conftrace_

bayesian neural network

201 papers

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Also known as

BNN

Co-occurring keywords

variational inference (2069) uncertainty quantification (1393) uncertainty estimation (648) gaussian process (1200) posterior distribution (259) posterior approximation (132) bayesian inference (1907) out-of-distribution detection (617) markov chain monte carlo (725) epistemic uncertainty (160)

Papers

Structured Stochastic Gradient MCMC ICML 2022
Nonlinear MCMC for Bayesian Machine Learning NIPS 2022
Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation NIPS 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks NIPS 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification NIPS 2022
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks AAAI 2022
Variational Model Perturbation for Source-Free Domain Adaptation NIPS 2022
Asymptotic Properties for Bayesian Neural Network in Besov Space NIPS 2022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022
Tractable Function-Space Variational Inference in Bayesian Neural Networks NIPS 2022
Function-space Inference with Sparse Implicit Processes ICML 2022
Asymptotics of representation learning in finite Bayesian neural networks NIPS 2021
Collapsed Variational Bounds for Bayesian Neural Networks NIPS 2021
Bayesian Experience Reuse for Learning from Multiple Demonstrators IJCAI 2021
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021
An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence NIPS 2021
Continuous-time Model-based Reinforcement Learning ICML 2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect NIPS 2021
High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021
Vector Quantized Bayesian Neural Network Inference for Data Streams AAAI 2021
Structured Dropout Variational Inference for Bayesian Neural Networks NIPS 2021
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon AISTATS 2021
Bayesian Inference with Certifiable Adversarial Robustness AISTATS 2021
Improving predictions of Bayesian neural nets via local linearization AISTATS 2021
Latent Derivative Bayesian Last Layer Networks AISTATS 2021