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11/23/2021
Uncertainty estimation under model misspecification in neural network regression
Although neural networks are powerful function approximators, the underl...
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10/12/2021
Uncertainty-based out-of-distribution detection requires suitable function space priors
The need to avoid confident predictions on unfamiliar data has sparked i...
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07/26/2021
Are Bayesian neural networks intrinsically good at out-of-distribution detection?
The need to avoid confident predictions on unfamiliar data has sparked i...
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06/22/2021
Repulsive Deep Ensembles are Bayesian
Deep ensembles have recently gained popularity in the deep learning comm...
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06/20/2021
On Stein Variational Neural Network Ensembles
Ensembles of deep neural networks have achieved great success recently, ...
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03/01/2021
Posterior Meta-Replay for Continual Learning
Continual Learning (CL) algorithms have recently received a lot of atten...
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01/24/2021
Annealed Stein Variational Gradient Descent
Particle based optimization algorithms have recently been developed as s...
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01/15/2020