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Huan Zhang's Projects

atla_robust_rl icon atla_robust_rl

Robust Reinforcement Learning with the Alternating Training of Learned Adversaries (ATLA) framework

certifiedrelurobustness icon certifiedrelurobustness

Efficient Robustness Verification for ReLU networks (this repository is outdated, don't use; checkout our new implementation at https://github.com/Verified-Intelligence/auto_LiRPA instead)

clever icon clever

CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks

compute icon compute

A C++ GPU Computing Library for OpenCL

crown-ibp icon crown-ibp

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

crown-robustness-certification icon crown-robustness-certification

CROWN: A Neural Network Robustness Certification Algorithm for General Activation Functions (This repository is outdated; use https://github.com/Verified-Intelligence/auto_LiRPA instead)

hogwildpp icon hogwildpp

HogWild++: A New Mechanism for Decentralized Asynchronous Stochastic Gradient Descent

hotspot-gpu icon hotspot-gpu

GPU accelerated version of the HotSpot simulator, a popular temperature modeling tool

lightgbm-gpu icon lightgbm-gpu

Development Repository for GPU-accelerated GBDT training

passcode-fix icon passcode-fix

Fixing convergence problems in Parallel ASynchronous Stochastic dual Co-ordinate Descent (PASSCoDe)

recurjac-and-crown icon recurjac-and-crown

Reference implementations for RecurJac, CROWN, FastLin and FastLip (Neural Network verification and robustness certification algorithms) [Do not use this repo, use https://github.com/Verified-Intelligence/auto_LiRPA instead]

sa_ddpg icon sa_ddpg

[NeurIPS 2020 Spotlight] State-adversarial DDPG for robust deep reinforcement learning

sa_ppo icon sa_ppo

[NeurIPS 2020 Spotlight] State-adversarial PPO for robust deep reinforcement learning

theano icon theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

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