Vibhav Gogate

Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization AAAI 2025 Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation CVPR 2025 A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models NeurIPS 2024 CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities NeurIPS 2024 Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification AISTATS 2024 Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains UAI 2024 Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models AISTATS 2024 Neural Network Approximators for Marginal MAP in Probabilistic Circuits AAAI 2024 Towards Scene Graph Anticipation ECCV 2024 A New Modeling Framework for Continuous, Sequential Domains AISTATS 2023 Knowledge Intensive Learning of Cutset Networks UAI 2023 Conditionally Tractable Density Estimation using Neural Networks AISTATS 2022 Learning Tractable Probabilistic Models from Inconsistent Local Estimates NeurIPS 2022 Robust learning of tractable probabilistic models UAI 2022 Dynamic Cutset Networks AISTATS 2021 Novel Upper Bounds for the Constrained Most Probable Explanation Task NeurIPS 2021 A Novel Approach for Constrained Optimization in Graphical Models NeurIPS 2020 Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models IJCAI 2019 Domain-Size Aware Markov Logic Networks AISTATS 2019 Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation ICML 2019 The 35th Uncertainty in Artificial Intelligence Conference: Preface UAI 2019 Algorithms for the Nearest Assignment Problem IJCAI 2018 Efficient Inference for Untied MLNs IJCAI 2017 Order Statistics for Probabilistic Graphical Models IJCAI 2017 Advanced Markov Logic Techniques for Scalable Joint Inference in NLP EMNLP 2016 Joint Inference for Event Coreference Resolution COLING 2016 Probabilistic Inference Modulo Theories IJCAI 2016 Lifted MAP Inference for Markov Logic Networks AISTATS 2014 Loopy Belief Propagation in the Presence of Determinism AISTATS 2014 Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features EMNLP 2014 The Inclusion-Exclusion Rule and Its Application to the Junction Tree Algorithm IJCAI 2013 On Lifting the Gibbs Sampling Algorithm NeurIPS 2012 Learning Efficient Markov Networks NeurIPS 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 On Combining Graph-based Variance Reduction schemes AISTATS 2010 SampleSearch: A Scheme that Searches for Consistent Samples AISTATS 1999