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12/09/2022
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization
Reliable uncertainty quantification in deep neural networks is very cruc...
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09/13/2021
Improving Robustness and Efficiency in Active Learning with Contrastive Loss
This paper introduces supervised contrastive active learning (SCAL) by l...
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09/13/2021
Mitigating Sampling Bias and Improving Robustness in Active Learning
This paper presents simple and efficient methods to mitigate sampling bi...
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12/14/2020
Improving model calibration with accuracy versus uncertainty optimization
Obtaining reliable and accurate quantification of uncertainty estimates ...
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11/15/2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Transparency of algorithmic systems entails exposing system properties t...
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12/03/2019
Deep Probabilistic Models to Detect Data Poisoning Attacks
Data poisoning attacks compromise the integrity of machine-learning mode...
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06/12/2019
MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks
Variational inference for Bayesian deep neural networks (DNNs) requires ...
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11/27/2018
Uncertainty aware multimodal activity recognition with Bayesian inference
Deep neural networks (DNNs) provide state-of-the-art results for a multi...
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11/08/2018