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03/31/2023
Long-Short Temporal Co-Teaching for Weakly Supervised Video Anomaly Detection
Weakly supervised video anomaly detection (WS-VAD) is a challenging prob...
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03/23/2023
Hierarchical Semantic Contrast for Scene-aware Video Anomaly Detection
Increasing scene-awareness is a key challenge in video anomaly detection...
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04/10/2022
Information-theoretic Online Memory Selection for Continual Learning
A challenging problem in task-free continual learning is the online sele...
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06/10/2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
We introduce a new scalable variational Gaussian process approximation w...
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11/06/2020
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
While uncertainty estimation is a well-studied topic in deep learning, m...
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08/20/2019
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes
The developments of Rademacher complexity and PAC-Bayesian theory have b...
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03/14/2019
Functional Variational Bayesian Neural Networks
Variational Bayesian neural networks (BNNs) perform variational inferenc...
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06/12/2018
Differentiable Compositional Kernel Learning for Gaussian Processes
The generalization properties of Gaussian processes depend heavily on th...
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06/07/2018
A Spectral Approach to Gradient Estimation for Implicit Distributions
Recently there have been increasing interests in learning and inference ...
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12/06/2017
Noisy Natural Gradient as Variational Inference
Combining the flexibility of deep learning with Bayesian uncertainty est...
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09/18/2017
ZhuSuan: A Library for Bayesian Deep Learning
In this paper we introduce ZhuSuan, a python probabilistic programming l...
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05/29/2017