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07/14/2023
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions
Accelerating the discovery of novel and more effective therapeutics is a...
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05/31/2023
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
Bayesian optimization is a highly efficient approach to optimizing objec...
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05/31/2023
Protein Design with Guided Discrete Diffusion
A popular approach to protein design is to combine a generative model wi...
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03/01/2023
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
In this paper, we provide an information-theoretic perspective on Varian...
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01/04/2023
On Sequential Bayesian Inference for Continual Learning
Sequential Bayesian inference can be used for continual learning to prev...
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12/28/2022
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations
KL-regularized reinforcement learning from expert demonstrations has pro...
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11/23/2022
Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks
Bayesian deep learning seeks to equip deep neural networks with the abil...
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06/09/2022
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations
Offline reinforcement learning has shown great promise in leveraging lar...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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04/20/2021
Outcome-Driven Reinforcement Learning via Variational Inference
While reinforcement learning algorithms provide automated acquisition of...
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11/01/2020
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes
We show that the gradient estimates used in training Deep Gaussian Proce...
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11/01/2020
Inter-domain Deep Gaussian Processes
Inter-domain Gaussian processes (GPs) allow for high flexibility and low...
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12/22/2019
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
Evaluation of Bayesian deep learning (BDL) methods is challenging. We of...
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02/11/2019
The StarCraft Multi-Agent Challenge
In the last few years, deep multi-agent reinforcement learning (RL) has ...
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12/05/2018
Multi^3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
We propose a novel approach for rapid segmentation of flooded buildings ...
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11/03/2018
