Talks
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and videos for the talks and papers below.
Recent Invited Talks, Tutorials
Recent Papers with Talks
2025 | |
| [232] | . Adversarial Tokenization, In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 2025. |
2024 | |
| [231] | . Where is the signal in tokenization space?, In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. Oral full presentation, acceptance rate 198/6105 = 3.2% |
| [230] | . Polynomial Semantics of Tractable Probabilistic Circuits, In Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI), 2024. Oral full presentation, acceptance rate 27/744 = 3.6% |
2022 | |
| [229] | . Lossless Compression with Probabilistic Circuits, In Proceedings of the International Conference on Learning Representations (ICLR), 2022. Oral spotlight presentation, acceptance rate 176/3391 = 5.2% |
| [228] | . Solving Marginal MAP Exactly by Probabilistic Circuit Transformations, In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022. |
2021 | |
| [227] | . Tractable Regularization of Probabilistic Circuits, In Advances in Neural Information Processing Systems 34 (NeurIPS), 2021. Oral spotlight presentation, acceptance rate 340/9122 = 3.7% |
| [226] | . A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference, In Advances in Neural Information Processing Systems 34 (NeurIPS), 2021. Oral full presentation, acceptance rate 55/9122 = 0.6% |
| [225] | . Probabilistic Sufficient Explanations, In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. |
| [224] | . Probabilistic Generating Circuits, In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. Long presentation, acceptance rate 166/5513 = 3% |
| [223] | . On the Tractability of SHAP Explanations, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. AAAI distinguished paper award |
| [222] | . Group Fairness by Probabilistic Modeling with Latent Fair Decisions, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. |
| [221] | . Logical Abstractions for Noisy Variational Quantum Algorithm Simulation, In Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2021. IEEE Micro top picks 2022 honorable mention |
2020 | |
| [220] | . 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% |
| [219] | . Counterexample-Guided Learning of Monotonic Neural Networks, In Advances in Neural Information Processing Systems 33 (NeurIPS), 2020. |
| [218] | . On Effective Parallelization of Monte Carlo Tree Search, In Deep Reinforcement Learning Workshop at NeurIPS (DRLW), 2020. |
Older Invited Talks, Tutorials, etc.
Invited Talk
— Nov 2021
Tractable Computation of Expected Kernels by Circuit Representations
Microsoft Research, New England
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