conftrace_

posterior approximation

132 papers

Explore in graph

Co-occurring keywords

variational inference (2069) bayesian inference (1907) bayesian neural network (201) markov chain monte carlo (725) uncertainty quantification (1393) approximate inference (253) amortized inference (102) gaussian process (1200) generative model (2892) normalizing flow (354)

Papers

A Targeted Accuracy Diagnostic for Variational Approximations AISTATS 2023
The Bayesian Learning Rule JMLR 2023
Gradient-Free Kernel Stein Discrepancy NIPS 2023
Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data ICML 2023
GPEX, A Framework For Interpreting Artificial Neural Networks NIPS 2023
Influence-Aware Attention for Multivariate Temporal Point Processes CLEAR 2023
MixFlows: principled variational inference via mixed flows ICML 2023
Variational Inference with Locally Enhanced Bounds for Hierarchical Models ICML 2022
Structured Stochastic Gradient MCMC ICML 2022
Structured variational inference in Bayesian state-space models AISTATS 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation NIPS 2022
A Probabilistic Framework for Land Deformation Prediction (Student Abstract) AAAI 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks NIPS 2022
Bayesian inference via sparse Hamiltonian flows NIPS 2022
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference AISTATS 2022
On the detrimental effect of invariances in the likelihood for variational inference NIPS 2022
Variational inference via Wasserstein gradient flows NIPS 2022
Bayesian structure learning with generative flow networks UAI 2022
Transfer Learning with Gaussian Processes for Bayesian Optimization AISTATS 2022
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference JMLR 2022
Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders CVPR 2022
Easy Variational Inference for Categorical Models via an Independent Binary Approximation ICML 2022
Variational Inference for Infinitely Deep Neural Networks ICML 2022
Posterior and Computational Uncertainty in Gaussian Processes NIPS 2022
Bayesian Deep Learning via Subnetwork Inference ICML 2021