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Variational Inference

105 directly classified papers

Papers per year

Papers

Rethinking Variational Inference for Probabilistic Programs with Stochastic Support NIPS 2022
Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units AAAI 2022
Learning Tractable Probabilistic Models from Inconsistent Local Estimates NIPS 2022
Treatment Effect Estimation with Disentangled Latent Factors AAAI 2021
Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021
Online Variational Filtering and Parameter Learning NIPS 2021
Variational Pedestrian Detection CVPR 2021
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021
Instance-Dependent Partial Label Learning NIPS 2021
Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021
Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation ACL 2021
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation NIPS 2020
NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations AAAI 2020
f-Divergence Variational Inference NIPS 2020
Meta-Amortized Variational Inference and Learning AAAI 2020
Capsule Routing via Variational Bayes AAAI 2020
Probabilistic Circuits for Variational Inference in Discrete Graphical Models NIPS 2020
A Variational Approach for Learning from Positive and Unlabeled Data NIPS 2020
Learning to Learn Variational Semantic Memory NIPS 2020
Total Deep Variation for Linear Inverse Problems CVPR 2020
Walsh-Hadamard Variational Inference for Bayesian Deep Learning NIPS 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models L4DC 2020
Introducing Routing Uncertainty in Capsule Networks NIPS 2020
Variance Reduction and Quasi-Newton for Particle-Based Variational Inference ICML 2020