Popular GitHub Repositories for Aistats

For deep RL and the future of AI.

Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)

Repository for the paper "Optimal design of stochastic DNA synthesis protocols based on generative sequence models" (Weinstein et al., AISTATS, 2022).

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

The official implementation of "Optimal Stochastic Trace Estimation in Generative Modeling (AISTATS 2025)"

Structured Multi-task Learning for Molecular Property Prediction, AISTATS'22 (https://proceedings.mlr.press/v151/liu22e.html)

Official code for Differentiable Rendering with Reparameterized Volume Sampling (AISTATS 2024)

Code repository for the robust active label correction paper.

Global-Local Regularization Via Distributional Robustness (AISTATS 2023)

Official code for "Federated Learning for Data Streams" (AISTATS'23)

PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).

Source code of the RIL-Co algorithm in AISTATS 2021 paper titled "Robust Imitation Learning from Noisy Demonstrations".

[AISTATS 2024] BOBA: Byzantine-Robust Federated Learning with Label Skewness. Wenxuan Bao, Jun Wu, Jingrui He

[AISTATS 2025] Rooted logistic loss to optimize neural network traning and LLM quantization

About Code repository for: Nguyen, H., Nguyen, T., Nguyen, K., & Ho, N. (2024). Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, AISTATS 2024, Acceptance rate 27.6% over 1980 submissions.

Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach, AISTATS 2024.

An unofficial implementation of Federated Learning: Communication-Efficient Learning of Deep Networks from Decentralized Data (AISTATS 2017)

[AISTATS 2024] Official Implementation of "Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach"

Local Competition and Stochasticity for Adversarial Robustness, AISTATS 2021

Source code for off-policy evaluation and optimization in the presence of unobserved confounding, accepted to AISTATS 2024.