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ai-feynman

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-deep-gnn

Papers about developing deep Graph Neural Networks (GNNs)

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-diffusion-models

A collection of resources and papers on Diffusion Models and Score-based Models, a darkhorse in the field of Generative Models

awesome-equivariant-network

Paper list for equivariant neural network

awesome-neural-geometry

A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond

awesome-normalizing-flows

A list of awesome resources on normalizing flows.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

benchmarking-gnns

Repository for benchmarking graph neural networks

constrained-hamiltonian-neural-networks

course-v3

The 3rd edition of course.fast.ai

course2019

course2020

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

delphes

A framework for fast simulation of a generic collider experiment

dig

A library for graph deep learning research

dysts

More than a hundred strange attractors

energyenergycorrelators

C++ code with a python wrapper for computing energy-energy correlators (EECs) efficiently

energyflow_ml

equivariant-mlp

flowtorch

This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially on complete infra and documentation for how to use and create components.

gauge-equivariant-mesh-cnn

geantsimulationforml

detector simulation for ML

geometry-central

Applied 3D geometry in C++, with a focus on surface meshes.

gnnpapers

Must-read papers on graph neural networks (GNN)

graph-neural-pde

Graph Neural PDEs

graph4nlp

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP

graphtransformer

Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.