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Variational Inference

105 directly classified papers

Papers per year

Papers

A Variational Approach for Learning from Positive and Unlabeled Data NIPS 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Walsh-Hadamard Variational Inference for Bayesian Deep Learning NIPS 2020
Learning to Learn Variational Semantic Memory NIPS 2020
Introducing Routing Uncertainty in Capsule Networks NIPS 2020
Probabilistic Circuits for Variational Inference in Discrete Graphical Models NIPS 2020
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation NIPS 2020
Stein Variational Gradient Descent With Matrix-Valued Kernels NIPS 2019
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference NIPS 2019
Variational Information Distillation for Knowledge Transfer CVPR 2019
Variational Convolutional Neural Network Pruning CVPR 2019
Variational BEJG Solvers for Marginal-MAP Inference with Accurate Approximation of B-Conditional Entropy AAAI 2019
Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms AAAI 2019
A Latent Variational Framework for Stochastic Optimization NIPS 2019
Universal Boosting Variational Inference NIPS 2019
Variational Inference and Deep Generative Models ACL 2018
Wasserstein Variational Inference NIPS 2018
Provable Variational Inference for Constrained Log-Submodular Models NIPS 2018
Tighter Variational Bounds are Not Necessarily Better ICML 2018
A Generative Parser with a Discriminative Recognition Algorithm ACL 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Robust Energy Minimization for BRDF-Invariant Shape From Light Fields CVPR 2017
Stein Variational Gradient Descent as Gradient Flow NIPS 2017
Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017
Collapsed variational Bayes for Markov jump processes NIPS 2017