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05/24/2023
Inverse Reinforcement Learning with the Average Reward Criterion
We study the problem of Inverse Reinforcement Learning (IRL) with an ave...
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11/11/2022
Inverse Kernel Decomposition
The state-of-the-art dimensionality reduction approaches largely rely on...
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04/14/2022
SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework
Multi-animal pose estimation is essential for studying animals' social b...
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10/12/2021
Domain Generalization via Domain-based Covariance Minimization
Researchers have been facing a difficult problem that data generation me...
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09/09/2021
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
Advances in neural recording present increasing opportunities to study n...
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05/11/2020
Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis
With the wide adoption of functional magnetic resonance imaging (fMRI) b...
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07/01/2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
Latent dynamics discovery is challenging in extracting complex dynamics ...
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10/09/2018
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks
Bayesian neural networks (BNNs) hold great promise as a flexible and pri...
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11/28/2017
Dependent relevance determination for smooth and structured sparse regression
In many problem settings, parameter vectors are not merely sparse, but d...
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03/31/2017
