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

Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions UAI 2019
Noise Contrastive Priors for Functional Uncertainty UAI 2019
Randomized Value Functions via Multiplicative Normalizing Flows UAI 2019
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning ICML 2018
Learning Structural Weight Uncertainty for Sequential Decision-Making AISTATS 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors ICML 2018
Assessing Quality Estimation Models for Sentence-Level Prediction COLING 2018
Variational Inference with Tail-adaptive f-Divergence NIPS 2018
Variational Bayesian dropout: pitfalls and fixes ICML 2018
Adversarial Distillation of Bayesian Neural Network Posteriors ICML 2018
Noisy Natural Gradient as Variational Inference ICML 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences ICML 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks ICML 2017
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes NIPS 2017
Natural-Parameter Networks: A Class of Probabilistic Neural Networks NIPS 2016
Bayesian Optimization with Robust Bayesian Neural Networks NIPS 2016
Rényi Divergence Variational Inference NIPS 2016
VIME: Variational Information Maximizing Exploration NIPS 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks ICML 2015
Variational Dropout and the Local Reparameterization Trick NIPS 2015