https://opencatalystproject.org/

A batched offline inference oriented version of segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

Python Sorted Container Types: Sorted List, Sorted Dict, and Sorted Set

PyTorch extensions for high performance and large scale training.

WhereWulff: An Automated Workflow to Democratize and Scale Complex Material Discovery for Electrocatalysis

A modular framework for neural networks with Euclidean symmetry

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Geometric Deep Learning Extension Library for PyTorch

A GPipe implementation in PyTorch

End-to-End Speech Processing Toolkit

PyTorch implementation of SENet

Assignments for CS294-112.

TensorFlow Neural Machine Translation Tutorial

A library for generalized sequence to sequence models

An implementation of the Globally Normalized Reader

A framework for training and evaluating AI models on a variety of openly available dialog datasets.

Implementation of End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures in ACL2016.

A general-purpose encoder-decoder framework for Tensorflow

Core Sketch Library.

A platform for developing AI systems as described in A Roadmap towards Machine Intelligence - http://arxiv.org/abs/1511.08130

Implementation of Sequence Generative Adversarial Nets with Policy Gradient

Efficient implementation of Wavenet generation.

Implementation of Newest RNN and Seq2Seq Features

Deep Learning Tutorial notes and code. See the wiki for more info.

A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.