Talks
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Recent Invited Talks, Tutorials
Invited Talk
— Nov 2021

Tractable Computation of Expected Kernels by Circuit Representations
Microsoft Research, New England
Recent Papers with Talks
2021 | |
[175] | On the Tractability of SHAP Explanations, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. . AAAI distinguished paper award |
[174] | Group Fairness by Probabilistic Modeling with Latent Fair Decisions, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. . |
2020 | |
[173] | Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations, In Advances in Neural Information Processing Systems 33 (NeurIPS), 2020. . Oral spotlight presentation, acceptance rate 385/9454 = 4.1% |
[172] | Counterexample-Guided Learning of Monotonic Neural Networks, In Advances in Neural Information Processing Systems 33 (NeurIPS), 2020. . |
[171] | On Effective Parallelization of Monte Carlo Tree Search, In Deep Reinforcement Learning Workshop at NeurIPS (DRLW), 2020. . |
[170] | SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning, In Conference on Robot Learning, 2020. . |
[169] | Scaling Exact Inference for Discrete Probabilistic Programs, In Proc. ACM Program. Lang. (OOPSLA), ACM, 2020. . ACM SIGPLAN distinguished paper award |
[168] | Relax, compensate and then integrate, In Proceedings of the ECML-PKDD Workshop on Deep Continuous-Discrete Machine Learning (DeCoDeML), 2020. . |
[167] | Strudel: Learning Structured-Decomposable Probabilistic Circuits, In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM), 2020. . |
[166] | On the Relationship Between Probabilistic Circuits and Determinantal Point Processes, In Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence (UAI), 2020. . |
[165] | Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings, In Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence (UAI), 2020. . |
[164] | Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing, In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020. . |
[163] | Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits, In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020. . |
[162] | Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration, In Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020. . |
[161] | Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams, In Proceedings of the Symposium on Intelligent Data Analysis (IDA), 2020. . |
Older Invited Talks, Tutorials, etc.
Tutorial
— May 2020

Probabilistic Circuits: Inference, Representations, Learning and Theory
UCLA Computer Science Department - CS201 Seminar
Invited Talk
— Jan 2020

Towards a New Synthesis of Reasoning and Learning
CSE Colloquia Series, Washington University in St. Louis
Invited Talk — Oct 2019
Colloquium Talk at Harvey Mudd College
Invited Talk
— Apr 2019

Towards a New Synthesis of Reasoning and Learning
Northeastern University, Khoury College of Computer Sciences
Invited Talk
— Feb 2019

Probabilistic and Logistic Circuits: A New Synthesis of Logic and Machine Learning
RelationalAI ArrowheadCon
Invited Talk
— May 2018

Probabilistic Circuits: A New Synthesis of Logic and Machine Learning
Computer Science Department, University of California, San Diego
Panelist — 2018
Women & Philanthropy Spring Event on Artificial Intelligence, University of California, Los Angeles
Talk
— 2017

PSDDs for Tractable Learning in Structured and Unstructured Spaces
Computer Science Department, University of British Columbia
Invited Talk
— 2016
Probabilistic Reasoning by First-Order Model Counting
Workshop on Uncertainty in Computation, Simons Institute, Berkeley
Invited Talk
— 2015

First-Order Knowledge Compilation for Probabilistic Reasoning
Symposium on New Frontiers in Knowledge Compilation, Vienna Center for Logic and Algorithms, Austria
Invited Tutorial — 2015
An Overview of Statistical Relational Learning
Alberto Mendelzon Graduate School on Data Management, Lima, Peru
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science, Cornell University
Invited Talk
— 2015
Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science & Engineering, University of Washington, Seattle
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science, University of Southern California
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science, University of California, Irvine
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Cheriton School of Computer Science, University of Waterloo
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Computer Sciences Department, University of Wisconsin-Madison
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science, Tufts University
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Department of Computer Science and Informatics, Indiana University, Bloomington
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne
Invited Talk
— 2015

Scalable Inference and Learning for High-Level Probabilistic Models
Computer Science Department, University of California, Los Angeles
Invited Tutorial
— 2014

Lifted inference in statistical relational models
International workshop on Big Uncertain Data (BUDA), ACM SIGMOD/PODS conference, Snowbird
Invited Talk — 2014
ECCAI Dissertation Award Ceremony at the European Conference on Artificial Intelligence (ECAI), , Prague, Czech Republic
Invited Talk — 2014
Scientific prize IBM Belgium for Informatics Award Ceremony, IBM, Brussels, Belgium
Invited Talk — 2014
Lifted Inference and Learning in Statistical Relational Models,
Center for Data Science, University of Washington, Tacoma
Talk
— 2012

Recent advances in lifted inference at Leuven
Spring Workshop on Mining and Learning, Bad Neuenahr, Germany
Invited Talk
— 2011

Monte-Carlo tree search for multi-player, no-limit Texas hold’em poker
SIKS Symposium on Strategic Decision-Making in Complex Games, Maastricht University, Netherlands