An educational resource to help anyone learn deep reinforcement learning.

A Python implementation of global optimization with gaussian processes.

Pytorch implementation of convolutional neural network visualization techniques

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

A Python toolbox for performing gradient-free optimization

Learning to Learn in TensorFlow

Code for visualizing the loss landscape of neural nets

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

A PyTorch Library for Meta-learning Research

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

Corruption and Perturbation Robustness (ICLR 2019)

ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

An open source python library for scalable Bayesian optimisation.

Robust evasion attacks against neural network to find adversarial examples

Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"

Code for the paper "Generative Adversarial Imitation Learning"

ImageNet classifier with state-of-the-art adversarial robustness

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

Countering Adversarial Image using Input Transformations.

A method for training neural networks that are provably robust to adversarial attacks.

Code for "One-Shot Visual Imitation Learning via Meta-Learning"

Label Refinery: Improving ImageNet Classification through Label Progression

A plug-in replacement for DataLoader to load Imagenet disk-sequentially in PyTorch.

Code for ICML 2019 paper "Simple Black-box Adversarial Attacks"

Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem [CVPR 2019, oral]

[ECCV 2020] PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

Code release for paper "Random Search and Reproducibility for NAS"