UAI 2023 Workshop TPM Submissions

Boosting AND/OR-Based Computational Protein Design: Dynamic Heuristics and Generalizable UFO
Bobak Pezeshki, Radu Marinescu, Alexander Ihler, Rina Dechter
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
LOFT - Stable Training of Normalizing Flows for Variational Inference
Daniel Andrade
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Bayesian Learning of Probabilistic Circuits with Domain Constraints
Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Causal normalizing flows: from theory to practice
Adrián Javaloy, Pablo Sanchez Martin, Isabel Valera
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
A Probabilistic Approach to Fairness under Label Bias
Saurav Anchlia, YooJung Choi
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Knowledge Intensive Learning of Cutset Networks
Saurabh Mathur, Vibhav Giridhar Gogate, Sriraam Natarajan
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Tractable Bounding of Counterfactual Queries by Knowledge Compilation
David Huber, Yizuo Chen, Alessandro Antonucci, Adnan Darwiche, Marco Zaffalon
- Published: 13 Jul 2023, Last Modified: 23 Aug 2023
- TPM 2023
- Readers: Everyone
Negative Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Stefan Mengel, Nicolas Gillis, Antonio Vergari
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Encoding Negative Dependencies in Probabilistic Circuits
Aleksanteri Mikulus Sladek, Martin Trapp, Arno Solin
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Unifying and Understanding Overparameterized Circuit Representations via Low-Rank Tensor Decompositions
Antonio Mari, Gennaro Vessio, Antonio Vergari
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Logarithm-Approximate Floating-Point Multiplier for Hardware-efficient Inference in Probabilistic Circuits
Lingyun Yao, Martin Trapp, Karthekeyan Periasamy, Jelin Leslin, Gaurav Singh, Martin Andraud
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
On test-time active feature selection through tractable acquisition functions
Athresh Karanam, Sriraam Natarajan
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference
Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Characteristic Circuit
Zhongjie Yu, Martin Trapp, Kristian Kersting
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Probabilistic Circuits That Know What They Don’t Know
Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Sum-Product-Set Networks
Milan Papez, Martin Rektoris, Tomáš Pevný, Vaclav Smidl
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
On Modal Clustering with Gaussian Sum-Product Networks
Tiago Madeira, Denis Mauá
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Long Horizon Temperature Scaling
Andy Shih, Dorsa Sadigh, Stefano Ermon
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone
Training and Inference on Any-Order Autoregressive Models the Right Way
Andy Shih, Dorsa Sadigh, Stefano Ermon
- Published: 13 Jul 2023, Last Modified: 22 Aug 2023
- TPM 2023
- Readers: Everyone