24 citations · 97 across the 26 of their papers we have counts for
16 papers · 1 filter
Towards an Interpretable Latent Space in Structured Models for Video Prediction
Rushil Gupta, Vishal Sharma, Yash Jain +3
We focus on the task of future frame prediction in video governed by underlying physical dynamics. We work with models which are object-centric, i.e., explicitly work with object r…
Tractable Regularization of Probabilistic Circuits
Anji Liu, Guy Van den Broeck
Probabilistic Circuits (PCs) are a promising avenue for probabilistic modeling. They combine advantages of probabilistic graphical models (PGMs) with those of neural networks (NNs)…
Probabilistic Sufficient Explanations
Eric Wang, Pasha Khosravi, Guy Van den Broeck
Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been propo…
Leveraging Unlabeled Data for Entity-Relation Extraction through Probabilistic Constraint Satisfaction
Kareem Ahmed, Eric Wang, Guy Van den Broeck +1
We study the problem of entity-relation extraction in the presence of symbolic domain knowledge. Such knowledge takes the form of an ontology defining relations and their permissib…
Tractable Computation of Expected Kernels
Wenzhe Li, Zhe Zeng, Antonio Vergari +1
Computing the expectation of kernel functions is a ubiquitous task in machine learning, with applications from classical support vector machines to exploiting kernel embeddings of…
Group Fairness by Probabilistic Modeling with Latent Fair Decisions
YooJung Choi, Meihua Dang, Guy Van den Broeck
Machine learning systems are increasingly being used to make impactful decisions such as loan applications and criminal justice risk assessments, and as such, ensuring fairness of…