Perturb-and-max-product: Sampling and learning in discrete energy-based
models

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Perturb-and-max-product: Sampling and learning in discrete energy-based models

3 November 2021

Miguel Lazaro-Gredilla

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Papers citing "Perturb-and-max-product: Sampling and learning in discrete energy-based models"

7 / 7 papers shown

Title
Discrete Neural Flow Samplers with Locally Equivariant Transformer Zijing Ou Ruixiang Zhang Yingzhen Li 76 0 0 23 May 2025
Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model Yuzhong Hong Hanshan Zhang Junwei Bao Hongfei Jiang Yang Song OffRL 117 4 0 18 Dec 2024
Circular Belief Propagation for Approximate Probabilistic Inference Vincent Bouttier R. Jardri S. Denéve 87 1 0 17 Mar 2024
Cyclic Group Projection for Enumerating Quasi-Cyclic Codes Trapping Sets V. Usatyuk Yury Kuznetsov Sergey Egorov 110 0 0 26 Jan 2024
Training Discrete Energy-Based Models with Energy Discrepancy Tobias Schröder Zijing Ou Yingzhen Li Andrew B. Duncan 56 0 0 14 Jul 2023
Topology-Aware Uncertainty for Image Segmentation Saumya Gupta Yikai Zhang Xiaoling Hu Prateek Prasanna Chao Chen 82 30 0 09 Jun 2023
Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation Antoine Dedieu Guangyao Zhou Dileep George Miguel Lazaro-Gredilla BDL 46 2 0 31 Jan 2023