## Talks

Click icons to see presentation *slides* and *videos* for the talks and papers below.

### 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 | |

[169] | On the Tractability of SHAP Explanations, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. . AAAI distinguished paper award |

[168] | Group Fairness by Probabilistic Modeling with Latent Fair Decisions, In Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021. . |

## 2020 | |

[167] | 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% |

[166] | Counterexample-Guided Learning of Monotonic Neural Networks, In Advances in Neural Information Processing Systems 33 (NeurIPS), 2020. . |

[165] | On Effective Parallelization of Monte Carlo Tree Search, In Deep Reinforcement Learning Workshop at NeurIPS (DRLW), 2020. . |

[164] | SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning, In Conference on Robot Learning, 2020. . |

[163] | Scaling Exact Inference for Discrete Probabilistic Programs, In Proc. ACM Program. Lang. (OOPSLA), ACM, 2020. . ACM SIGPLAN distinguished paper award |

[162] | Relax, compensate and then integrate, In Proceedings of the ECML-PKDD Workshop on Deep Continuous-Discrete Machine Learning (DeCoDeML), 2020. . |

[161] | Strudel: Learning Structured-Decomposable Probabilistic Circuits, In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM), 2020. . |

[160] | On the Relationship Between Probabilistic Circuits and Determinantal Point Processes, In Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence (UAI), 2020. . |

[159] | Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings, In Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence (UAI), 2020. . |

[158] | 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. . |

[157] | Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits, In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020. . |

[156] | 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. . |

[155] | 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 holdâ€™em poker

SIKS Symposium on Strategic Decision-Making in Complex Games, Maastricht University, Netherlands