Accepted Papers
- Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Patrik Reizinger, Luigi Gresele, Jack Brady, Julius Von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve
GatherTown Poster ID: D1
- Why Is This an Outlier? Explaining Outliers by Submodular Optimization of Marginal Distributions
Pasha Khosravi, Antonio Vergari, Guy Van den Broeck
GatherTown Poster ID: D2
- Tractable Uncertainty for Structure Learning
Benjie Wang, Matthew Robert Wicker, Marta Kwiatkowska
GatherTown Poster ID: D3
- Learning Linear Non-Gaussian Polytree Models
Daniele Tramontano, Mathias Drton, Anthea Monod
- Efficient Learning Losses for Deep Hinge-Loss Markov Random Fields
Charles Andrew Dickens, Connor Pryor, Eriq Augustine, Alon Albalak, Lise Getoor
- AND/OR Branch-and-Bound for Computational Protein Design Optimizing K*
Bobak Pezeshki, Radu Marinescu, Alexander Ihler, Rina Dechter
- Towards Tractable Dynamic Decision Making With Circuits
Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
- Learning Large Bayesian Networks with Expert Constraints
Vaidyanathan P. Ramaswamy, Stefan Szeider
GatherTown Poster ID: D4
- On Priors in Bayesian Probabilistic Circuits and Multivariate Pólya Trees
Martin Trapp, Arno Solin
GatherTown Poster ID: E5
- Reducing the Cost of Fitting Mixture Models via Stochastic Sampling
Milan Papez, Tomáš Pevný, Vaclav Smidl
- Towards Coreset Learning in Probabilistic Circuits
Martin Trapp, Steven Lang, Aastha Shah, Martin Mundt, Kristian Kersting, Arno Solin
GatherTown Poster ID: F5
- Tensorised Probabilistic Inference for Neural Probabilistic Logic Programming
Lennert De Smet, Robin Manhaeve, Giuseppe Marra, Pedro Zuidberg Dos Martires
- Predictive Whittle Networks for Time Series
Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting
GatherTown Poster ID: D5
- Sum-Product-Attention Networks: Leveraging Self-Attention in Energy-Based Probabilistic Circuits
Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting
GatherTown Poster ID: G1
- Certifying Fairness of Probabilistic Circuits
Nikil Roashan Selvam, Guy Van den Broeck, YooJung Choi
GatherTown Poster ID: G2
- Explaining Deep Tractable Probabilistic Models: The sum-product network case
Athresh Karanam, Saurabh Mathur, David M Haas, Predrag Radivojac, Kristian Kersting, Sriraam Natarajan
GatherTown Poster ID: E1
- Semantic Probabilistic Layers for Neuro-Symbolic Learning
Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
- Neuro-Symbolic Entropy Regularization
Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck
GatherTown Poster ID: G3
- Your Knowledge Graph Embeddings are Secretly Circuits and You Should Treat Them as Such
Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
GatherTown Poster ID: G4
- Learning Cutset Networks by Integrating Data and Noisy, Local Estimates
Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Giridhar Gogate
GatherTown Poster ID: F1
- Robust Learning of Tractable Probabilistic Models
Rohith Peddi, Tahrima Rahman, Vibhav Giridhar Gogate
- Exploiting Inferential Structure in Neural Processes
Dharmesh Tailor, Mohammad Emtiyaz Khan, Eric Nalisnick
- Generating Heavy-Tailed Synthetic Data with Normalizing Flows
Saba Amiri, Eric Nalisnick, Adam Belloum, Sander Klous, Leon Gommans
GatherTown Poster ID: G5
- Sparse Probabilistic Circuits via Pruning and Growing
Meihua Dang, Anji Liu, Guy Van den Broeck
GatherTown Poster ID: C1
- Bayesian Weak Supervision via an Optimal Transport Approach
Putra Manggala, Holger Hoos, Eric Nalisnick
- Distributionally Robust Learning of Sum-Product Networks
Rohith Peddi, Vibhav Giridhar Gogate