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Variational Inference

1,952 papers

Papers per year

2
9
31
252
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Papers

A theory of continuous generative flow networks ICML 2023
Conditional Graph Information Bottleneck for Molecular Relational Learning ICML 2023
Structured Cooperative Learning with Graphical Model Priors ICML 2023
Variational Open-Domain Question Answering ICML 2023
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits ICML 2023
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification ICML 2023
Generative Decoding of Visual Stimuli ICML 2023
Learn to Accumulate Evidence from All Training Samples: Theory and Practice ICML 2023
Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts ICML 2023
Modality-Agnostic Variational Compression of Implicit Neural Representations ICML 2023
Variational Autoencoding Neural Operators ICML 2023
Neural Markov Jump Processes ICML 2023
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates ICML 2023
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows ICML 2023
Latent Traversals in Generative Models as Potential Flows ICML 2023
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks ICML 2023
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes ICML 2023
Robust Weak Supervision with Variational Auto-Encoders ICML 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes ICML 2023
Random Grid Neural Processes for Parametric Partial Differential Equations ICML 2023
Vector Quantized Wasserstein Auto-Encoder ICML 2023
A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging ICML 2023
MixFlows: principled variational inference via mixed flows ICML 2023
Bit Allocation using Optimization ICML 2023
Self-Interpretable Time Series Prediction with Counterfactual Explanations ICML 2023