free energy

Free Energy of Bayesian Convolutional Neural Network with Skip Connection ACML 2023 Particle algorithms for maximum likelihood training of latent variable models AISTATS 2023 Active Learning for Domain Adaptation: An Energy-Based Approach AAAI 2022 Gardner formula for Ising perceptron models at small densities COLT 2022 Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks JMLR 2022 On Linear Model with Markov Signal Priors AISTATS 2022 Surprise Minimizing Multi-Agent Learning with Energy-based Models NeurIPS 2022 Contrastive Active Inference NeurIPS 2021 A Free-Energy Principle for Representation Learning ICML 2020 Deep active inference agents using Monte-Carlo methods NeurIPS 2020 Free Energy Wells and Overlap Gap Property in Sparse PCA COLT 2020 Diagnosing and Enhancing VAE Models ICLR 2019 The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity COLT 2018 The Benefits of Learning with Strongly Convex Approximate Inference ICML 2015 Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NeurIPS 2015 Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NeurIPS 2014 Approximating the Permanent with Fractional Belief Propagation JMLR 2013 Free energy score space NeurIPS 2009 Expectation Consistent Approximate Inference JMLR 2005