Instituto de Matemática e Estatística da USP

Denis Deratani Mauá

É Professor Associado do Departamento de Ciência da Computação do Instituto de Matemática e Estatística da Universidade de São Paulo. Tem experiência na área de Inteligência Artificial, em especial no estudo de modelos probabilísticos baseados em grafos e suas aplicações. Obteve doutorado pela Università della Svizzera Italiana (Suíça) em 2013. Possui mestrado em Engenharia Mecatrônica (2009) e diploma de Engenharia Elétrica com ênfase em Automação e Controle (2007), ambos pela Escola Politécnica da Universidade de São Paulo. Entre 2009 e 2013 foi pesquisador no Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA) em Lugano, Suíça. Foi pós-doutorando no Laboratório de Tomada de Decisão da Escola Politécnica da Universidade de São Paulo. (Texto informado pelo autor)

  • http://lattes.cnpq.br/5302472310971255 (03/02/2025)
  • Rótulo/Grupo:
  • Bolsa CNPq: Nível 2
  • Período de análise:
  • Endereço: Universidade de São Paulo, Instituto de Matemática e Estatística, Departamento de Ciência da Computação. Rua do Matão 1010 Butantã 05508090 - São Paulo, SP - Brasil Telefone: (11) 30915036 URL da Homepage: http://www.ime.usp.br/~ddm
  • Grande área: Ciências Exatas e da Terra
  • Área: Ciência da Computação
  • Citações: Google Acadêmico

Produção bibliográfica

Produção técnica

Produção artística

Orientações em andamento

Supervisões e orientações concluídas

Projetos de pesquisa

Prêmios e títulos

Participação em eventos

Organização de eventos

Lista de colaborações


Produção bibliográfica

Produção técnica

Produção artística

Orientações em andamento

Supervisões e orientações concluídas

Projetos de pesquisa

Prêmios e títulos

  • Total de prêmios e títulos (8)
    1. Melhor Dissertação de Mestrado no XXXVI Concurso de Teses e Dissertações (CTD) do CSBC 2023 - Orientador, Sociedade Brasileira de Computação (SBC).. 2023.
      Membro: Denis Deratani Mauá.
    2. Segundo Melhor Artigo da 11th Brazilian Conference on Intelligent Systems (BRACIS), SBC.. 2022.
      Membro: Denis Deratani Mauá.
    3. Melhor Dissertação de Mestrado em Inteligência Artificial no 13º Concurso de Teses e Dissertações em Inteligência Artificial e Computacional (CTDIAC) - Orientador, Comissão Especial em IA da Sociedade Brasileira de Computação.. 2022.
      Membro: Denis Deratani Mauá.
    4. Google Latin American Research Award, Google.. 2018.
      Membro: Denis Deratani Mauá.
    5. Terceiro melhor artigo no 5th Symposium On Knowledge Discovery, Mining and Learning (KDMiLe 2017)., SBC.. 2017.
      Membro: Denis Deratani Mauá.
    6. ISIPTA-IJAR Young Research Award - Golden Prize, SIPTA IJAR.. 2015.
      Membro: Denis Deratani Mauá.
    7. Best Paper Award, XII Encontro Nacional de Inteligencia Artificial e Computacional (ENIAC 2015).. 2015.
      Membro: Denis Deratani Mauá.
    8. Google Best Student Paper Award at UAI, Association for the Advancement of Artificial Intelligence.. 2013.
      Membro: Denis Deratani Mauá.

Participação em eventos

  • Total de participação em eventos (18)
    1. Eleventh International Symposium on Imprecise Probabilities: Theories and Applications. Robust Analysis of MAP Inference in Selective Sum-Product Networks. 2019. (Congresso).
    2. 2018 7th Brazilian Conference on Intelligent Systems (BRACIS). 2018. (Congresso).
    3. 5th Brazilian Conference on Intelligent System. 2016. (Congresso).
    4. Eight International Conference on Probabilistic Graphical Models. The Effect of Combination Functions on the Complexity of Relational Bayesian Networks. 2016. (Congresso).
    5. XIII Encontro Nacional de Inteligência Artificial e Computacional. Improving Acyclic Selection Order-Based Bayesian Network Structure Learning. 2016. (Congresso).
    6. 24th International Joint Conference on Artificial Intelligence (IJCAI 2015). The Complexity of MAP with Bayesian Networks Specified by Logic Constructs. 2015. (Congresso).
    7. 2014 Brazilian Conference on Intelligent Systems (BRACIS). Hidden Markov Models with Set-Valued Parameters. 2014. (Congresso).
    8. The Seventh European Workshop on Probabilistic Graphic Models.Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams. 2014. (Oficina).
    9. 6th Workshop on Principles and Methods of Statistical Inference with Interval Probability ity.Inference algorithms for credal networks. 2013. (Oficina).
    10. Doctoral Consortium at International Joint Conference on Artificial Intelligence (IJCAI-13). Approximation Algorithms for Max-Sum-Product Problems. 2013. (Congresso).
    11. International Joint Conference on Artificial Intelligence (IJCAI-13). An ensemble of Bayesian networks for multilabel classification. 2013. (Congresso).
    12. Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-12). The Complexity of Approximately Solving Influence Diagrams. 2012. (Congresso).
    13. International Conference on Machine Learning (ICML-12). Anytime marginal map inference. 2012. (Congresso).
    14. Advances in Neural Information Processing Systems (NIPS-11). Solving Decision Problems with Limited Information. 2011. (Congresso).
    15. International Symposium on Imprecise Probability: Theories and Applications (ISPTA-11). A Fully Polynomial Time Approximation Scheme for Updating Credal Networks of Bounded Treewidth and Number of Variable States. 2011. (Congresso).
    16. 3rd Workshop on Principles and Methods of Statistical Inference with Interval Probabilityility.Bucket Elimination in Credal Networks: Exact and Approximation Algorithms. 2010. (Oficina).
    17. IV Workshop on MSc Dissertation and PhD Thesis in Artificial Intelligence (WTDIA).Managing Trust in Virtual Communities with Markov Logic. 2008. (Oficina).
    18. Workshop on Information Visualization and Analysis in Social Networks.Using Social Data to Predict Trust on Web Communities. 2008. (Oficina).

Organização de eventos

  • Total de organização de eventos (2)
    1. BARROS, L. N. ; MAUA, DENIS DERATANI. Escola Regional de Aprendizado de Máquina e Inteligência Artificial. 2020. Outro
    2. MAUA, DENIS DERATANI; NALDI, M.. Encontro Nacional de Inteligência Artificial e Computacional. 2018. Congresso

Lista de colaborações

  • Colaborações endôgenas (2)
    • Denis Deratani Mauá ⇔ Denis Deratani Mauá (111.0)
      1. DE ALENCAR, JÚLIO CÉSAR GARCIA ; STERNLICHT, JULIANA MARTES ; VEIGA, ALICIA DUDY MULLER ; MARCHINI, JULIO FLÁVIO MEIRELLES ; FERREIRA, JULIANA CARVALHO ; DE CARVALHO, CARLOS ROBERTO RIBEIRO ; MARCILIO, IZABEL ; DA SILVA, KATIA REGINA ; COBELLO JUNIOR, VILSON ; FELIX, MARCELO CONSORTI ; GOMEZ, LUZ MARINA GOMEZ ; DE SOUZA, HERALDO POSSOLO ; MAUÁ, DENIS DERATANI. Timing to Intubation COVID-19 Patients: Can We Put It Off until Tomorrow?. Healthcare. v. 10, p. 206, 2022. Qualis: C
      2. SAAD MENEZES, MARIA CLARA ; SANTINELLI PESTANA, DIEGO VINICIUS ; FERREIRA, JULIANA CARVALHO ; RIBEIRO DE CARVALHO, CARLOS ROBERTO ; FELIX, MARCELO CONSORTI ; MARCILIO, IZABEL OLIVA ; DA SILVA, KATIA REGINA ; JUNIOR, VILSON COBELLO ; MARCHINI, JULIO FLAVIO ; ALENCAR, JULIO CESAR ; GOMEZ, LUZ MARINA GOMEZ ; MAUÁ, DENIS DERATANI ; SOUZA, HERALDO POSSOLO. Distinct Outcomes in COVID-19 Patients with Positive or Negative RT-PCR Test. Viruses-Basel. v. 14, p. 175, 2022. Qualis: Não identificado (VIRUSES-BASEL)
      3. MOREIRA, DANIEL A.M. ; VALDIVIA DELGADO, KARINA ; de Barros, Leliane Nunes ; DERATANI MAUÁ, DENIS. Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 139, p. 143-165, 2021. Qualis: A1
      4. MAUÁ, DENIS DERATANI; DE CAMPOS, CASSIO POLPO. Special Issue on Robustness in Probabilistic Graphical Models. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 137, p. 113, 2021. Qualis: A1
      5. MAUÁ, DENIS DERATANI; COZMAN, FABIO GAGLIARDI. Complexity results for probabilistic answer set programming. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 118, p. 133-154, 2020. Qualis: A1
      6. MATTEI, LILITH ; ANTONUCCI, ALESSANDRO ; MAUÁ, DENIS DERATANI ; FACCHINI, ALESSANDRO ; VILLANUEVA LLERENA, JULISSA. Tractable inference in credal sentential decision diagrams. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 125, p. 26-48, 2020. Qualis: A1
      7. COZMAN, FABIO GAGLIARDI ; MAUÁ, DENIS DERATANI. The joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 125, p. 218-239, 2020. Qualis: A1
      8. VILLANUEVA LLERENA, JULISSA ; MAUÁ, DENIS DERATANI. Efficient Algorithms for Robustness Analysis of Maximum A Posteriori Inference in Selective Sum-Product Networks. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 126, p. 158-180, 2020. Qualis: A1
      9. MAUÁ, DENIS DERATANI; COZMAN, FABIO GAGLIARDI. Thirty years of credal networks: Specification, algorithms and complexity. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 126, p. 133-157, 2020. Qualis: A1
      10. VIEIRA DE FARIA, FRANCISCO H.O. ; GUSMÃO, ARTHUR COLOMBINI ; DE BONA, GLAUBER ; MAUÁ, DENIS DERATANI ; COZMAN, FABIO GAGLIARDI. Speeding up parameter and rule learning for acyclic probabilistic logic programs. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 106, p. 32-50, 2019. Qualis: A1
      11. COZMAN, FABIO GAGLIARDI ; MAUÁ, DENIS DERATANI. The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 110, p. 107-126, 2019. Qualis: A1
      12. COZMAN, FABIO G. ; Mauá, Denis D.. The complexity of Bayesian networks specified by propositional and relational languages. ARTIFICIAL INTELLIGENCE. v. 262, p. 96-141, 2018. Qualis: A1
      13. DERATANI MAUÁ, DENIS; CONATY, DIARMAID ; GAGLIARDI COZMAN, FABIO ; POPPENHAEGER, KATJA ; POLPO DE CAMPOS, CASSIO. Robustifying sum-product networks. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 101, p. 163-180, 2018. Qualis: A1
      14. GAGLIARDI COZMAN, FABIO ; DERATANI MAUÁ, DENIS. On the complexity of propositional and relational credal networks. International Journal of Approximate Reasoning. v. 83, p. 298-319, 2017. Qualis: A1
      15. MAUÁ, DENIS DERATANI; COZMAN, FABIO GAGLIARDI. The effect of combination functions on the complexity of relational Bayesian networks. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 85, p. 178-195, 2017. Qualis: A1
      16. COZMAN, FABIO G. ; MAUÁ, DENIS DERATANI. On the Semantics and Complexity of Probabilistic Logic Programs. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH. v. 60, p. 221-262, 2017. Qualis: A2 (THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH)
      17. MAUÁ, DENIS DERATANI; ANTONUCCI, ALESSANDRO ; DE CAMPOS, CASSIO POLPO. Hidden Markov models with set-valued parameters. Neurocomputing (Amsterdam). v. 180, p. 94-107, 2016. Qualis: A2
      18. Walter Perez ; MAUA, DENIS DERATANI. Better Initialization Heuristics for Order-based Bayesian Network Structure Learning. Journal of Information and Data Management - JIDM. v. 7, p. 181-195, 2016.Qualis: B3
      19. MAUÁ, DENIS DERATANI; COZMAN, FABIO GAGLIARDI. Fast local search methods for solving limited memory influence diagrams. International Journal of Approximate Reasoning,. p. 230-245, 2015. Qualis: A1 (INTERNATIONAL JOURNAL OF APPROXIMATE REASONING)
      20. MAUÁ, DENIS DERATANI. Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams. International Journal of Approximate Reasoning,. p. 211-229, 2015. Qualis: A1 (INTERNATIONAL JOURNAL OF APPROXIMATE REASONING)
      21. MAUÁ, D. D.; DE CAMPOS, CASSIO P. ; BENAVOLI, A. ; ANTONUCCI, A.. Probabilistic Inference in Credal Networks: New Complexity Results. The Journal of Artificial Intelligence Research (Print). v. 50, p. 603-637, 2014.Qualis: A2
      22. MAUÁ, D. D.; C. P. de Campos ; Zaffalon, M.. On the Complexity of Solving Polytree-Shaped Limited Memory Influence Diagrams with Binary Variables. Artificial Intelligence (General Ed.),. p. 30-38, 2013. Qualis: A1 (ARTIFICIAL INTELLIGENCE)
      23. MAUÁ, D. D.; C. P. de Campos ; Zaffalon, M.. Solving Limited Memory Influence Diagrams. The Journal of Artificial Intelligence Research (Print). v. 44, p. 97-140, 2012. Qualis: A2
      24. MAUÁ, DENIS D.; DE CAMPOS, CASSIO P. ; ZAFFALON, MARCO. Updating credal networks is approximable in polynomial time. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 53, p. 1183-1199, 2012. Qualis: A1
      25. ZAFFALON, MARCO ; CORANI, GIORGIO ; MAUÁ, DENIS. Evaluating credal classifiers by utility-discounted predictive accuracy. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 53, p. 1282-1301, 2012. Qualis: A1
      26. CATANEO SILVEIRA, IGOR ; BARBOSA, A. ; COSTA, D. S. L. ; MAUA, DENIS D.. Investigating Universal Adversarial Attacks Against Transformers-Based Automatic Essay Scoring Systems. Lecture Notes in Computer Science. 1ed. Em: . : Springer Nature Switzerland. 2025.p. 169-183.
      27. Rocha, Victor Hugo Nascimento ; Silveira, Igor Cataneo ; Pirozelli, Paulo ; MAUÁ, DENIS DERATANI ; COZMAN, FABIO GAGLIARDI. Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks. Lecture Notes in Computer Science. 1ed. Em: . : Springer Nature Switzerland. 2023.p. 428-440.
      28. JOSE, M. M. ; JOSE, M. A. ; MAUÁ, D. D. ; COZMAN, F. G.. Integrating Question Answering and Text-to-SQL in Portuguese. Em: Vládia Pinheiro, Pablo Gamallo, Raquel Amaro, Carolina Scarton, Fernando Batista, Diego Silva, Catarina Magro, Hugo Pinto. (Org.). Integrating Question Answering and Text-to-SQL in Portuguese. 1ed. : Lecture Notes in Computer Science,. 2022.v. 13208, p. 278-287.
      29. Lovatto, Ângelo ; BARROS, L. N. ; DERATANI MAUÁ, DENIS. Exploration Versus Exploitation in Model-Based Reinforcement Learning: An Empirical Study. Intelligent Systems. BRACIS 2022. Lecture Notes in Computer Science(). 1ed.Berlin. Em: Xavier-Junior, J.C., Rios, R.A.. (Org.). Lecture Notes in Computer Science: Intelligent Systems. BRACIS 2022.. 1ed. : Springer. 2022.v. 13654, p. 30-44.
      30. MONEDA, L. ; DERATANI MAUÁ, DENIS. Time Robust Trees: Using Temporal Invariance to Improve Generalization. Em: Xavier-Junior, J.C., Rios, R.A.. (Org.). Lecture Notes in Computer Science: Intelligent Systems. BRACIS 2022. 1ed. : Springer. 2022.v. 13653, p. 385-397.
      31. LLERENA, JULISSA VILLANUEVA ; MAUÁ, DENIS DERATANI ; ANTONUCCI, ALESSANDRO. Cautious Classification with Data Missing Not at Random Using Generative Random Forests. Lecture Notes in Computer Science. 1ed. Em: . : Springer International Publishing. 2021.v. 12897, p. 284-298.
      32. Scaroni, Renato ; BUENO, THIAGO P. ; de Barros, Leliane N. ; MAUÁ, DENIS. On the Performance of Planning Through Backpropagation. Lecture Notes in Computer Science. 1ed. Em: Cerri, R.;Prati, R.C.. (Org.). Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science(). 1ed.Berlin. : Springer International Publishing. 2020.v. 12320, p. 108-122.
      33. Fernandez, Milton Condori ; de Barros, Leliane N. ; MAUÁ, DENIS ; Delgado, Karina V. ; Freire, Valdinei. Finding Feasible Policies for Extreme Risk-Averse Agents in Probabilistic Planning. Lecture Notes in Computer Science. 1ed. Em: Cerri, R.; Prati, R.C.. (Org.). Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science. Serie LNAI. 1ed.Berlin. : Springer International Publishing. 2020.v. 12320, p. 497-508.
      34. SILVEIRA ; BARBOSA, A. ; MAUÁ, DENIS DERATANI. A New Benchmark for Automatic Essay Scoring in Portuguese. Em: International Conference on Computational Processing of Portuguese, v. 1, p. 228-237, 2024. Qualis: Não identificado (International Conference on Computational Processing of Portuguese)
      35. DERATANI MAUÁ, DENIS; COZMAN, FABIO G. ; GARCES, A.. Probabilistic Logic Programming under the L-Stable Semantics. Em: 22nd International Workshop on Nonmonotonic Reasoning (NMR 2024), v. 3835, p. 24-33, 2024.Qualis: Não identificado (22nd International Workshop on Nonmonotonic Reasoning (NMR 2024))
      36. GEH, RENATO LUI ; GONÇALVES, JONAS ; SILVEIRA, IGOR C. ; Mauá, Denis D. ; COZMAN, FABIO G.. dPASP: A Probabilistic Logic Programming Environment For Neurosymbolic Learning and Reasoning. Em: 21st International Conference on Principles of Knowledge Representation and Reasoning {KR2023}, p. 731-742, 2024. Qualis: Não identificado (21st International Conference on Principles of Knowledge Representation and Reasoning {KR2023})
      37. WANG, B. ; MAUÁ, DENIS DERATANI ; BROECK, G. V. D. ; CHOI, Y.. A Compositional Atlas for Algebraic Circuits. Em: Neural Information Processing Systems (NeurIPS), 2024.Qualis: Não identificado (Neural Information Processing Systems (NeurIPS))
      38. Mauá, Denis D.; Fabio Cozman. Specifying credal sets with probabilistic answer set programming. Em: International Symposium on Imprecise Probability: Theories and Applications, v. 215, p. 321-332, 2023.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications)
      39. PENNACCHIO, ALAN A. ; BARROS, LELIANE N. DE ; MAUÁ, DENIS D.. Differentiable Planning for Optimal Liquidation. Em: Brazilian Workshop on Artificial Intelligence in Finance, p. 48-57, 2022. Qualis: Não identificado (Brazilian Workshop on Artificial Intelligence in Finance)
      40. MADEIRA, T. ; DERATANI MAUÁ, DENIS. Tractable Mode-Finding in Sum-Product Networks with Gaussian Leaves. Em: XIX ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL, p. 497-508, 2022. Qualis: Não identificado (XIX ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL)
      41. DIAS, DANIEL B. ; N. de Barros, Leliane ; V. DELGADO, KARINA ; MAUÁ, DENIS D.. Differentiable Planning with Indefinite Horizon. Em: Symposium on Knowledge Discovery, v. 10, p. 170-177, 2022. Qualis: Não identificado (Symposium on Knowledge Discovery)
      42. VILLANUEVA, JULISSA ; MAUÁ, DENIS. Tractable Classification with Non-Ignorable Missing Data Using Generative Random Forests. Em: Symposium on Knowledge Discovery, p. 42-49, 2022. Qualis: Não identificado (Symposium on Knowledge Discovery)
      43. GEH, R. L. ; MAUA, DENIS DERATANI. Fast And Accurate Learning of Probabilistic Circuits by Random Projections. Em: 4th Workshop on Tractable Probabilistic Modeling, 2021.Qualis: Não identificado (4th Workshop on Tractable Probabilistic Modeling)
      44. GEH, R. L. ; MAUA, DENIS DERATANI. Learning probabilistic sentential decision diagrams under logic constraints by sampling and averaging. Em: Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, v. 161, p. 2039-2049, 2021.Qualis: Não identificado (Thirty-Seventh Conference on Uncertainty in Artificial Intelligence)
      45. THOMAZ, Guilherme ; MAUA, DENIS DERATANI ; BARROS, LELIANE N. DE. A Contact Network-Based Approach for Online Planning of Containment Measures for COVID-19. Em: XVII Encontro Nacional de Inteligência Artificial e Computacional, v. 17, p. 234-245, 2020. Qualis: Não identificado (XVII Encontro Nacional de Inteligência Artificial e Computacional)
      46. GEH, R. L. ; MAUA, DENIS DERATANI ; ANTONUCCI, A.. Learning Probabilistic Sentential Decision Diagrams by Sampling. Em: VIII Symposium on Knowledge Discovery, p. 129-136, 2020. Qualis: Não identificado (VIII Symposium on Knowledge Discovery)
      47. NETTO, Caio ; TANNURI, Eduardo ; MAUA, DENIS DERATANI ; COZMAN, FABIO G.. Prediction of Environmental Conditions for Maritime Navigation using a Network of Sensors: A Practical Application of Graph Neural Networks. Em: VIII Symposium on Knowledge Discovery, p. 233-240, 2020. Qualis: Não identificado (VIII Symposium on Knowledge Discovery)
      48. MAUA, DENIS DERATANI; Reis, Heitor Ribeiro ; Katague, Gustavo Perez ; ANTONUCCI, A.. Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks. Em: 10th International Conference on Probabilistic Graphical Models, v. 138, p. 293-304, 2020.Qualis: Não identificado (10th International Conference on Probabilistic Graphical Models)
      49. GEH, RENATO ; MAUÁ, DENIS. End-To-End Imitation Learning of Lane Following Policies Using Sum-Product Networks. Em: XVI Encontro Nacional de Inteligência Artificial e Computacional, p. 297, 2019. Qualis: Não identificado (XVI Encontro Nacional de Inteligência Artificial e Computacional)
      50. BUENO, THIAGO P. ; BARROS, LELIANE N. DE ; MAUA, DENIS DERATANI ; SANNER, S.. Deep Reactive Policies for Planning in Stochastic Nonlinear Domains. Em: Thirty-Third AAAI Conference on Artificial Intelligence, 2019.Qualis: Não identificado (Thirty-Third AAAI Conference on Artificial Intelligence)
      51. LLERENA, JULISSA VILLANUEVA ; MAUA, DENIS DERATANI. Robust Analysis of MAP Inference in Selective Sum-Product Networks. Em: Eleventh International Symposium on Imprecise Probabilities: Theories and Applications, v. 103, p. 430-440, 2019.Qualis: Não identificado (Eleventh International Symposium on Imprecise Probabilities: Theories and Applications)
      52. MATTEI, L. ; SOARES, D. L. ; ANTONUCCI, ALESSANDRO ; MAUÁ, DENIS D. ; FACCHINI, A.. Exploring the Space of Probabilistic Sentential Decision Diagrams. Em: 3rd Tractable Probabilistic Modeling Workshop, 2019.Qualis: Não identificado (3rd Tractable Probabilistic Modeling Workshop)
      53. COZMAN, FABIO GAGLIARDI ; MAUÁ, DENIS DERATANI. The Finite Model Theory of Bayesian Networks: Descriptive Complexity. Em: TwentySeventh International Joint Conference on Artificial Intelligence {IJCAI18}, p. 5229-5233, 2018. Qualis: Não identificado (TwentySeventh International Joint Conference on Artificial Intelligence {IJCAI18})
      54. Andrés, Igansi ; BARROS, L. N. ; MAUÁ, DENIS ; Simões, Thiago Dias. When a Robot Reaches out for Human Help. Em: 16th Ibero-American Conference on Artificial Intelligence (IBERAMIA), p. 277-289, 2018.Qualis: Não identificado (16th Ibero-American Conference on Artificial Intelligence (IBERAMIA))
      55. CATANEO SILVEIRA, IGOR ; DERATANI MAUA, DENIS. Advances in Automatically Solving the ENEM. Em: 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), p. 43, 2018. Qualis: Não identificado (2018 7th Brazilian Conference on Intelligent Systems (BRACIS))
      56. CONATY, D. ; Mauá, Denis D. ; C. P. de Campos. Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks. Em: Thirty-Third Conference on Uncertainty in Artificial Intelligence, p. 322-331, 2017.Qualis: Não identificado (Thirty-Third Conference on Uncertainty in Artificial Intelligence)
      57. FARIA, F. H. O. V. ; COZMAN, FABIO G. ; MAUÁ, DENIS DERATANI. Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization. Em: International Conference on Scalable Uncertainty Management, p. 19-133, 2017.Qualis: Não identificado (International Conference on Scalable Uncertainty Management)
      58. MAUÁ, DENIS DERATANI; COZMAN, FABIO G. ; CONATY, D. ; C. P. de Campos. Credal Sum-Product Networks. Em: International Symposium on Imprecise Probability: Theories and Applications, v. 62, p. 205-216, 2017.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications)
      59. COZMAN, FABIO G. ; Denis Maua. The Descriptive Complexity of Bayesian Network Specifications. Em: European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, p. 93-103, 2017.Qualis: Não identificado (European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty)
      60. COZMAN, FABIO G. ; Denis Deratani Mauá. The Complexity of Inferences and Explanations in Probabilistic Logic Programming. Em: European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, p. 449-458, 2017.Qualis: Não identificado (European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty)
      61. LLERENA, JULISSA VILLANUEVA ; MAUA, DENIS DERATANI. On Using Sum-Product Networks for Multi-label Classification. Em: 2017 Brazilian Conference on Intelligent Systems (BRACIS), p. 25, 2017. Qualis: Não identificado (2017 Brazilian Conference on Intelligent Systems (BRACIS))
      62. SILVEIRA ; Denis Deratani Mauá. University Entrance Exam as a Guiding Test for Artificial Intelligence. Em: 2017 Brazilian Conference on Intelligent Systems (BRACIS), p. 426-431, 2017.Qualis: Não identificado (2017 Brazilian Conference on Intelligent Systems (BRACIS))
      63. FARIA, F. H. O. V. ; GUSMAO, A. C. ; Glauber de Bona ; Denis Deratani Mauá ; Fabio Cozman. Parameter Learning in ProbLog with Probabilistic Rules. Em: Symposium on knowledge Discovery, p. 27-34, 2017.Qualis: Não identificado (Symposium on knowledge Discovery)
      64. BUENO, THIAGO P. ; MAUA, DENIS DERATANI ; BARROS, LELIANE N. DE ; COZMAN, FABIO G.. Modeling Markov Decision Processes with Imprecise Probabilities Using Probabilistic Logic Programming. Em: International Symposium on Imprecise Probability: Theories and Applications (ISIPTA), v. 62, p. 49-60, 2017.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications (ISIPTA))
      65. COZMAN, FABIO GAGLIARDI ; MAUA, DENIS DERATANI. Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity. Em: Eighth International Conference on Probabilistic Graphical Models, v. 52, p. 110-122, 2016.Qualis: Não identificado (Eighth International Conference on Probabilistic Graphical Models)
      66. MAUA, DENIS DERATANI; COZMAN, FABIO GAGLIARDI. The Effect of Combination Functions on the Complexity of Relational Bayesian Networks. Em: Eighth International Conference on Probabilistic Graphical Models, v. 52, p. 333-344, 2016.Qualis: Não identificado (Eighth International Conference on Probabilistic Graphical Models)
      67. COZMAN, FABIO GAGLIARDI ; MAUA, DENIS DERATANI. The Structure and Complexity of Credal Semantics. Em: 3rd International Workshop on Probabilistic Programming, p. 3-14, 2016.Qualis: Não identificado (3rd International Workshop on Probabilistic Programming)
      68. BUENO, THIAGO P. ; MAUA, DENIS D. ; BARROS, LELIANE N. DE ; COZMAN, FABIO G.. Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution. Em: 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), p. 337, 2016. Qualis: Não identificado (2016 5th Brazilian Conference on Intelligent Systems (BRACIS))
      69. Fabio Cozman ; MAUÁ, DENIS D.. Bayesian Networks Specified Using Propositional and Relational Constructs: Combined, Data, and Domain Complexity. Em: Twenty-Ninth AAAI Conference on Artificial Intelligence, p. 3519-3525, 2015.Qualis: Não identificado (Twenty-Ninth AAAI Conference on Artificial Intelligence)
      70. MAUÁ, DENIS D.; C. P. de Campos ; Fabio Cozman. The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages. Em: 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), v. 0, p. 889-895, 2015.Qualis: Não identificado (24th International Joint Conference on Artificial Intelligence (IJCAI 2015))
      71. MAUÁ, DENIS D.; Fabio Cozman. On the complexity of propositional and relational credal networks. Em: Ninth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA), p. 97-105, 2015.Qualis: Não identificado (Ninth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA))
      72. Fabio Cozman ; Mauá, Denis D.. The Complexity of Plate Probabilistic Models. Em: Ninth International Conference on Scalable Uncertainty Management, v. 9310, p. 36-49, 2015.Qualis: Não identificado (Ninth International Conference on Scalable Uncertainty Management)
      73. Mauá, Denis D.; Fabio Cozman. DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model. Em: Ninth International Conference on Scalable Uncertainty Management, v. 9310, p. 50-64, 2015.Qualis: Não identificado (Ninth International Conference on Scalable Uncertainty Management)
      74. Mauá, Denis D.; Fabio Cozman. A Tractable Class of Model Counting. Em: XII Encontro Nacional de Inteligência Artificial e Computacional, 2015.Qualis: Não identificado (XII Encontro Nacional de Inteligência Artificial e Computacional)
      75. Fabio Cozman ; Mauá, Denis D.. Specifying Probabilistic Relational Models with Description Logics. Em: XII Encontro Nacional de Inteligencia Artificial e Computacional, 2015.Qualis: Não identificado (XII Encontro Nacional de Inteligencia Artificial e Computacional)
      76. Fabio Machado ; Mauá, Denis D. ; Fabio Cozman. Bayesian Networks of Bounded Treewith: A Performance Analysis. Em: XII Encontro Nacional de Inteligência Artificial e Computacional, 2015.Qualis: Não identificado (XII Encontro Nacional de Inteligência Artificial e Computacional)
      77. Walter Perez ; Mauá, Denis D.. Initialization Heuristics for Greedy Bayesian Network Structure Learning. Em: Third Symposium on Knowledge Discovery, p. 58-65, 2015.Qualis: Não identificado (Third Symposium on Knowledge Discovery)
      78. ANTONUCCI, A. ; SCANAGATTA, M. ; Mauá, Denis D. ; C. P. de Campos. Early classification of time series by hidden Markov models with set-valued parameters. Em: NIPS Times Series Workshop, 2015.Qualis: Não identificado (NIPS Times Series Workshop)
      79. CORANI, GIORGIO ; ANTONUCCI, A. ; MAUÁ, DENIS D. ; GABAGLIO, S.. Trading off Speed and Accuracy in Multilabel Classification. Em: 7th European Workshop on Probabilistic Graphical Models, p. 145-159, 2014.Qualis: Não identificado (7th European Workshop on Probabilistic Graphical Models)
      80. MAUÁ, DENIS D. Equivalences between Maximum a Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams. Em: 7th European Workshop on Probabilistic Graphical Models, p. 318-333, 2014.Qualis: Não identificado (7th European Workshop on Probabilistic Graphical Models)
      81. MAUÁ, DENIS D.; Fabio Cozman. Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams. Em: 7th European Workshop on Probabilistic Graphical Models, p. 334-349, 2014.Qualis: Não identificado (7th European Workshop on Probabilistic Graphical Models)
      82. Siqi Nie ; MAUÁ, DENIS D. ; C. P. de Campos ; Qian Ji. Advances in Learning Bayesian Networks of Bounded Treewidth. Em: Advances in Neural Information Processing Systems 27 (NIPS 2014), p. 2285-2293, 2014.Qualis: Não identificado (Advances in Neural Information Processing Systems 27 (NIPS 2014))
      83. MAUA, DENIS DERATANI; CAMPOS, CASSIO POLPO DE ; ANTONUCCI, ALESSANDRO. Algorithms for Hidden Markov Models with Imprecisely Specified Parameters. Em: 2014 Brazilian Conference on Intelligent Systems (BRACIS), p. 186, 2014. Qualis: Não identificado (2014 Brazilian Conference on Intelligent Systems (BRACIS))
      84. ANTONUCCI, A. ; CORANI, GIORGIO ; MAUÁ, D. D. ; GABAGLIO, S.. An ensemble of Bayesian networks for multilabel classification. Em: International Joint Conference on Artificial Intelligence (IJCAI-13), p. 1220-1225, 2013.Qualis: Não identificado (International Joint Conference on Artificial Intelligence (IJCAI-13))
      85. MAUÁ, D. D.; DE CAMPOS, CASSIO P. ; BENAVOLI, A. ; ANTONUCCI, A.. On the Complexity of Strong and Epistemic Credal Networks. Em: Conference on Uncertainty in Artificial Intelligence (UAI-13), p. 391-400, 2013.Qualis: Não identificado (Conference on Uncertainty in Artificial Intelligence (UAI-13))
      86. MAUÁ, D. D.; DE CAMPOS, CASSIO P.. Anytime marginal map inference. Em: International Conference on Machine Learning (ICML-12), p. 1471-1478, 2012.Qualis: Não identificado (International Conference on Machine Learning (ICML-12))
      87. MAUÁ, D. D.; C. P. de Campos ; Zaffalon, M.. The Complexity of Approximately Solving Influence Diagrams. Em: Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-12), p. 604-613, 2012.Qualis: Não identificado (Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-12))
      88. MAUÁ, D. D.; C. P. de Campos. Solving Decision Problems with Limited Information. Em: Advances in Neural Information Processing Systems (NIPS-11), p. 603-611, 2011.Qualis: Não identificado (Advances in Neural Information Processing Systems (NIPS-11))
      89. MAUÁ, D. D.; C. P. de Campos ; Zaffalon, M.. A Fully Polynomial Time Approximation Scheme for Updating Credal Networks of Bounded Treewidth and Number of Variable States. Em: International Symposium on Imprecise Probability: Theories and Applications (ISPTA-11), p. 277-286, 2011.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications (ISPTA-11))
      90. Zaffalon, M. ; CORANI, GIORGIO ; MAUÁ, D. D.. Utility-Based Accuracy Measures to Empirically Evaluate Credal Classifiers. Em: International Symposium on Imprecise Probability: Theories and Applications (ISPTA-11), p. 401-410, 2011.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications (ISPTA-11))
      91. MAUÁ, D. D.; Fabio Cozman. Using Social Data to Predict Trust on Web Communities. Em: Workshop on Information Visualization and Analysis in Social Networks, 2008.Qualis: Não identificado (Workshop on Information Visualization and Analysis in Social Networks)
      92. MAUÁ, D. D.; Fabio Cozman. Managing Trust in Virtual Communities with Markov Logic. Em: IV Workshop on MSc Dissertation and PhD Thesis in Artificial Intelligence (WTDIA), 2008.Qualis: Não identificado (IV Workshop on MSc Dissertation and PhD Thesis in Artificial Intelligence (WTDIA))
      93. MAUÁ, D. D. Approximation Algorithms for Max-Sum-Product Problems. Em: Doctoral Consortium at International Joint Conference on Artificial Intelligence (IJCAI-13), 2013, Beijing, China. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Menlo Park, California: AAAI Press / International Joint Conferences on Artificial Intelligence, p. 3235-3236, 2013. Qualis: Não identificado (DOCTORAL CONSORTIUM AT INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE , 2013, BEIJING, CHINA. PROCEEDINGS OF THE TWENTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE. MENLO PARK, CALIFORNIA: AAAI PRESS / INTERNATIONAL JOINT CONFERENCES ON ARTIFICIAL INTELLIGENCE)
      94. MAUÁ, D. D.; BAPTISTA, C. M. ; SILVEIRA, R. M. ; RUGGIERO, W. V.. Ferramenta Multimídia Interativa para Aprendizado Eletrônico. 2006. Apresentação de Trabalho/Simpósio
      95. Alexandre da Silva ; MAUÁ, D. D. ; Rafael Lopez. Reconhecimento Automático de Dígitos Falados. 2006. Trabalho de Formatura
      96. MAUÁ, D. D. kPu: A local search solver for limited memory influence diagrams. 2014.
      97. MAUÁ, D. D. iHMM: A C++ library for inference in hidden Markov models with imprecise parameters. 2014.
      98. MAUÁ, DENIS DERATANI. Membro do comitê de Programa da Conference on Uncertainty in Artificial Intelligence (UAI). 2017.
      99. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Joint Conference on Artificial Intelligence (IJCAI). 2017.
      100. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Conference on Imprecise Probability: Theory and Applications (ISIPTA). 2017.
      101. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Joint Conference on Artificial Intelligence (IJCAI). 2016.
      102. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da AAAI Conference on Artificial Intelligence (AAAI). 2016.
      103. MAUÁ, DENIS DERATANI. Membro do comitê de Programa da Conference on Uncertainty in Artificial Intelligence (UAI). 2016.
      104. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Conference on Probabilistic Graphical Models (PGM). 2016.
      105. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da Brazilian Conference on Computational and Intelligent Systems (BRACIS). 2016.
      106. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Joint Conference on Artificial Intelligence (IJCAI). 2015.
      107. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da AAAI Conference on Artificial Intelligence (AAAI). 2015.
      108. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da Conference on Uncertainty in Artificial Intelligence (UAI). 2015.
      109. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa da International Conference on Imprecise Probability: Theory and Applications (ISIPTA). 2015.
      110. MAUÁ, DENIS DERATANI. Membro do Comitê de Programa do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC). 2014.
      111. ANTONUCCI, A. ; CORANI, GIORGIO ; MAUÁ, D. D.. Bayesian networks with imprecise probabilities: theory and applications to knowledge-based systems and classification. 2013. Curso de curta duração ministrado/Outra

    • Denis Deratani Mauá ⇔ Leliane Nunes de Barros (10.0)
      1. MOREIRA, DANIEL A.M. ; VALDIVIA DELGADO, KARINA ; de Barros, Leliane Nunes ; DERATANI MAUÁ, DENIS. Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. v. 139, p. 143-165, 2021. Qualis: A1
      2. Lovatto, Ângelo ; BARROS, L. N. ; DERATANI MAUÁ, DENIS. Exploration Versus Exploitation in Model-Based Reinforcement Learning: An Empirical Study. Intelligent Systems. BRACIS 2022. Lecture Notes in Computer Science(). 1ed.Berlin. Em: Xavier-Junior, J.C., Rios, R.A.. (Org.). Lecture Notes in Computer Science: Intelligent Systems. BRACIS 2022.. 1ed. : Springer. 2022.v. 13654, p. 30-44.
      3. Scaroni, Renato ; BUENO, THIAGO P. ; de Barros, Leliane N. ; MAUÁ, DENIS. On the Performance of Planning Through Backpropagation. Lecture Notes in Computer Science. 1ed. Em: Cerri, R.;Prati, R.C.. (Org.). Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science(). 1ed.Berlin. : Springer International Publishing. 2020.v. 12320, p. 108-122.
      4. Fernandez, Milton Condori ; de Barros, Leliane N. ; MAUÁ, DENIS ; Delgado, Karina V. ; Freire, Valdinei. Finding Feasible Policies for Extreme Risk-Averse Agents in Probabilistic Planning. Lecture Notes in Computer Science. 1ed. Em: Cerri, R.; Prati, R.C.. (Org.). Intelligent Systems. BRACIS 2020. Lecture Notes in Computer Science. Serie LNAI. 1ed.Berlin. : Springer International Publishing. 2020.v. 12320, p. 497-508.
      5. PENNACCHIO, ALAN A. ; BARROS, LELIANE N. DE ; MAUÁ, DENIS D.. Differentiable Planning for Optimal Liquidation. Em: Brazilian Workshop on Artificial Intelligence in Finance, p. 48-57, 2022. Qualis: Não identificado (Brazilian Workshop on Artificial Intelligence in Finance)
      6. DIAS, DANIEL B. ; N. de Barros, Leliane ; V. DELGADO, KARINA ; MAUÁ, DENIS D.. Differentiable Planning with Indefinite Horizon. Em: Symposium on Knowledge Discovery, v. 10, p. 170-177, 2022. Qualis: Não identificado (Symposium on Knowledge Discovery)
      7. THOMAZ, Guilherme ; MAUA, DENIS DERATANI ; BARROS, LELIANE N. DE. A Contact Network-Based Approach for Online Planning of Containment Measures for COVID-19. Em: XVII Encontro Nacional de Inteligência Artificial e Computacional, v. 17, p. 234-245, 2020. Qualis: Não identificado (XVII Encontro Nacional de Inteligência Artificial e Computacional)
      8. Andrés, Igansi ; BARROS, L. N. ; MAUÁ, DENIS ; Simões, Thiago Dias. When a Robot Reaches out for Human Help. Em: 16th Ibero-American Conference on Artificial Intelligence (IBERAMIA), p. 277-289, 2018.Qualis: Não identificado (16th Ibero-American Conference on Artificial Intelligence (IBERAMIA))
      9. BUENO, THIAGO P. ; MAUA, DENIS DERATANI ; BARROS, LELIANE N. DE ; COZMAN, FABIO G.. Modeling Markov Decision Processes with Imprecise Probabilities Using Probabilistic Logic Programming. Em: International Symposium on Imprecise Probability: Theories and Applications (ISIPTA), v. 62, p. 49-60, 2017.Qualis: Não identificado (International Symposium on Imprecise Probability: Theories and Applications (ISIPTA))
      10. BUENO, THIAGO P. ; MAUA, DENIS D. ; BARROS, LELIANE N. DE ; COZMAN, FABIO G.. Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution. Em: 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), p. 337, 2016. Qualis: Não identificado (2016 5th Brazilian Conference on Intelligent Systems (BRACIS))




(*) Relatório criado com produções desde 2000 até 2025
Data de processamento: 25/02/2025 19:39:44