[NeurIPS 2025 Spotlight] Reasoning Environments for Reinforcement Learning with Verifiable Rewards

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

Examples and guides for using the OpenAI API

Enterprise Scale NLP with Hugging Face & SageMaker Workshop series

Large-scale, multi-GPU capable, kernel solver

Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"

Implementation for the Neural Logic Machines (NLM).

TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Regularization, Neural Network Training Dynamics

Bayesian Deep Learning Benchmarks

Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019

A minimalistic and high-performance SAT solver

Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry Benchmark, ICLR 2019

Computing various norms/measures on over-parametrized neural networks

A Python toolbox for performing gradient-free optimization

CaDiCaL SAT Solver

Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)

3.41% and 17.11% error on CIFAR-10 and CIFAR-100

A community repository for benchmarking Bayesian methods

Max-value Entropy Search for Efficient Bayesian Optimization

A highly efficient implementation of Gaussian Processes in PyTorch

Kernel structure discovery research code - likely to be unstable

A best practice for tensorflow project template architecture.

Forward-mode Automatic Differentiation for TensorFlow

A curated list of resources dedicated to bayesian deep learning