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

On the effects of quantisation on model uncertainty in Bayesian neural networks UAI 2021
Post-hoc loss-calibration for Bayesian neural networks UAI 2021
Ensembling geophysical models with Bayesian Neural Networks NIPS 2020
Learning Model with Error -- Exposing the Hidden Model of BAYHENN IJCAI 2020
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification INTERSPEECH 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks NIPS 2020
On the Expressiveness of Approximate Inference in Bayesian Neural Networks NIPS 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NIPS 2020
f-Divergence Variational Inference NIPS 2020
Probabilistic Safety for Bayesian Neural Networks UAI 2020
Uncertainty in Neural Networks: Approximately Bayesian Ensembling AISTATS 2020
Thompson Sampling via Local Uncertainty ICML 2020
Leveraging Document-Level Label Consistency for Named Entity Recognition IJCAI 2020
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes AAAI 2020
Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning ACML 2020
Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020
PoRB-Nets: Poisson Process Radial Basis Function Networks UAI 2020
Defense Through Diverse Directions ICML 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning AISTATS 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC AISTATS 2020
Model Fusion with Kullback-Leibler Divergence ICML 2020
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift ICML 2020
Uncertainty Modeling for Machine Comprehension Systems using Efficient Bayesian Neural Networks COLING 2020
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes JMLR 2020
Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020