2591 Repositories
Python graph-neural-networks Libraries
banditml is a lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
banditml is a lightweight contextual bandit & reinforcement learning library designed to be used in production Python services. This library is developed by Bandit ML and ex-authors of Facebook's applied reinforcement learning platform, Reagent.
small collection of functions for neural networks
neurobiba other languages: RU small collection of functions for neural networks. very easy to use! Installation: pip install neurobiba See examples h
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.09
Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset. This Neural Network (NN) model recognizes the text contained in the images of segmented words.
Handwritten-Text-Recognition Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset. T
Unofficial TensorFlow implementation of Protein Interface Prediction using Graph Convolutional Networks.
[TensorFlow] Protein Interface Prediction using Graph Convolutional Networks Unofficial TensorFlow implementation of Protein Interface Prediction usin
The source code of the paper "Understanding Graph Neural Networks from Graph Signal Denoising Perspectives"
GSDN-F and GSDN-EF This repository provides a reference implementation of GSDN-F and GSDN-EF as described in the paper "Understanding Graph Neural Net
Sharpness-Aware Minimization for Efficiently Improving Generalization
Sharpness-Aware-Minimization-TensorFlow This repository provides a minimal implementation of sharpness-aware minimization (SAM) (Sharpness-Aware Minim
Pytorch implementation of MaskFlownet
MaskFlownet-Pytorch Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet). Tested with: PyTorch 1.5.0 CUDA 10.1
Code for paper: Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks
Group-CAM By Zhang, Qinglong and Rao, Lu and Yang, Yubin [State Key Laboratory for Novel Software Technology at Nanjing University] This repo is the o
Benchmarks for semi-supervised domain generalization.
Semi-Supervised Domain Generalization This code is the official implementation of the following paper: Semi-Supervised Domain Generalization with Stoc
Neural Factorization of Shape and Reflectance Under An Unknown Illumination
NeRFactor [Paper] [Video] [Project] This is the authors' code release for: NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown I
Degree-Quant: Quantization-Aware Training for Graph Neural Networks.
Degree-Quant This repo provides a clean re-implementation of the code associated with the paper Degree-Quant: Quantization-Aware Training for Graph Ne
Subdivision-based Mesh Convolutional Networks
Subdivision-based Mesh Convolutional Networks The official implementation of SubdivNet in our paper, Subdivion-based Mesh Convolutional Networks Requi
Paddle implementation for "Highly Efficient Knowledge Graph Embedding Learning with Closed-Form Orthogonal Procrustes Analysis" (NAACL 2021)
ProcrustEs-KGE Paddle implementation for Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis 🙈 A more detailed re
PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"
Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati
Boosted neural network for tabular data
XBNet - Xtremely Boosted Network Boosted neural network for tabular data XBNet is an open source project which is built with PyTorch which tries to co
Pytorch Implementation of DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (TTS Extension)
DiffSinger - PyTorch Implementation PyTorch implementation of DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (TTS Extension). Status
Deep learning-based approach to discovering Granger causality networks in multivariate time series
Granger causality discovery for neural networks.
Code for the paper "How Attentive are Graph Attention Networks?"
How Attentive are Graph Attention Networks? This repository is the official implementation of How Attentive are Graph Attention Networks?. The PyTorch
Pytorch implementation of Generative Models as Distributions of Functions 🌿
Generative Models as Distributions of Functions This repo contains code to reproduce all experiments in Generative Models as Distributions of Function
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug
Official code for "Mean Shift for Self-Supervised Learning"
MSF Official code for "Mean Shift for Self-Supervised Learning" Requirements Python = 3.7.6 PyTorch = 1.4 torchvision = 0.5.0 faiss-gpu = 1.6.1 In
A tensorflow implementation of GCN-LPA
GCN-LPA This repository is the implementation of GCN-LPA (arXiv): Unifying Graph Convolutional Neural Networks and Label Propagation Hongwei Wang, Jur
Code release to accompany paper "Geometry-Aware Gradient Algorithms for Neural Architecture Search."
Geometry-Aware Gradient Algorithms for Neural Architecture Search This repository contains the code required to run the experiments for the DARTS sear
A supplementary code for Editable Neural Networks, an ICLR 2020 submission.
Editable neural networks A supplementary code for Editable Neural Networks, an ICLR 2020 submission by Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Py
Implementation for Simple Spectral Graph Convolution in ICLR 2021
Simple Spectral Graph Convolutional Overview This repo contains an example implementation of the Simple Spectral Graph Convolutional (S^2GC) model. Th
NR-GAN: Noise Robust Generative Adversarial Networks
NR-GAN: Noise Robust Generative Adversarial Networks (CVPR 2020) This repository provides PyTorch implementation for noise robust GAN (NR-GAN). NR-GAN
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing This repository contains pytorch source code for AAAI2020 oral paper: Grapy-ML
An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.
Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021
AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration
jaxfg - Factor graph-based nonlinear optimization library for JAX.
Factor graphs + nonlinear optimization in JAX
Explore related sequences in the OEIS
OEIS explorer This is a tool for exploring two different kinds of relationships between sequences in the OEIS: mentions (links) of other sequences on
whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.
whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.
Official PyTorch implementation for "Mixed supervision for surface-defect detection: from weakly to fully supervised learning"
Mixed supervision for surface-defect detection: from weakly to fully supervised learning [Computers in Industry 2021] Official PyTorch implementation
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling For Official repo of NU-Wave: A Diffusion Probabilistic Model for Neural Audio Up
Deep functional residue identification
DeepFRI Deep functional residue identification Citing @article {Gligorijevic2019, author = {Gligorijevic, Vladimir and Renfrew, P. Douglas and Koscio
Pytorch implementation of AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks
AngularGrad Optimizer This repository contains the oficial implementation for AngularGrad: A New Optimization Technique for Angular Convergence of Con
Code for KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs Check out the paper on arXiv: https://arxiv.org/abs/2103.13744 This repo cont
neurodsp is a collection of approaches for applying digital signal processing to neural time series
neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also includes simulation tools for generating plausible simulations of neural time series.
Deep Learning Visuals contains 215 unique images divided in 23 categories
Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide".
Code for our paper "Mask-Align: Self-Supervised Neural Word Alignment" in ACL 2021
Mask-Align: Self-Supervised Neural Word Alignment This is the implementation of our work Mask-Align: Self-Supervised Neural Word Alignment. @inproceed
Implementation of Bidirectional Recurrent Independent Mechanisms (Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules)
BRIMs Bidirectional Recurrent Independent Mechanisms Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neura
Tensorflow implementation for Self-supervised Graph Learning for Recommendation
If the compilation is successful, the evaluator of cpp implementation will be called automatically. Otherwise, the evaluator of python implementation will be called.
Codes for our IJCAI21 paper: Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization
DDAMS This is the pytorch code for our IJCAI 2021 paper Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization [Arxiv Pr
Implementation of the paper "Shapley Explanation Networks"
Shapley Explanation Networks Implementation of the paper "Shapley Explanation Networks" at ICLR 2021. Note that this repo heavily uses the experimenta
This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.
LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian
Repo for "Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks"
Summary This is the code for the paper Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks by Yanxiang Wang, Xian Zh
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
An Unsupervised Graph-based Toolbox for Fraud Detection
An Unsupervised Graph-based Toolbox for Fraud Detection Introduction: UGFraud is an unsupervised graph-based fraud detection toolbox that integrates s
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"
When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi
Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Expressive Power of Invariant and Equivaraint Graph Neural Networks (ICLR 2021)
Expressive Power of Invariant and Equivaraint Graph Neural Networks In this repository, we show how to use powerful GNN (2-FGNN) to solve a graph alig
PyTorch implementation of the paper Deep Networks from the Principle of Rate Reduction
Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl
Inference code for "StylePeople: A Generative Model of Fullbody Human Avatars" paper. This code is for the part of the paper describing video-based avatars.
NeuralTextures This is repository with inference code for paper "StylePeople: A Generative Model of Fullbody Human Avatars" (CVPR21). This code is for
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"
GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale
XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf
Deep learning (neural network) based remote photoplethysmography: how to extract pulse signal from video using deep learning tools
Deep-rPPG: Camera-based pulse estimation using deep learning tools Deep learning (neural network) based remote photoplethysmography: how to extract pu
Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.
This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. This implementation is written in JAX, and is a fork of Google's JaxNeRF implementation. Contact Jon Barron if you encounter any issues.
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021)
mlp-mixer-pytorch PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021) Usage import torch from mlp_mixer
NeRF Meta-Learning with PyTorch
NeRF Meta Learning With PyTorch nerf-meta is a PyTorch re-implementation of NeRF experiments from the paper "Learned Initializations for Optimizing Co
Code for ICML 2021 paper: How could Neural Networks understand Programs?
OSCAR This repository contains the source code of our ICML 2021 paper How could Neural Networks understand Programs?. Environment Run following comman
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.
python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu
[CVPR21] LightTrack: Finding Lightweight Neural Network for Object Tracking via One-Shot Architecture Search
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search The official implementation of the paper LightTra
Vision Transformer for 3D medical image registration (Pytorch).
ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition
Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors.
PairRE Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors. This implementation of PairRE for Open Graph Benchmak datasets (
Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks
This is the code associated with the paper Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks, published at CVPR 2020.
Neural Dynamic Policies for End-to-End Sensorimotor Learning
This is a PyTorch based implementation for our NeurIPS 2020 paper on Neural Dynamic Policies for end-to-end sensorimotor learning.
The pytorch implementation of DG-Font: Deformable Generative Networks for Unsupervised Font Generation
DG-Font: Deformable Generative Networks for Unsupervised Font Generation The source code for 'DG-Font: Deformable Generative Networks for Unsupervised
Espresso: A Fast End-to-End Neural Speech Recognition Toolkit
Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning libra
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation This repository contains the original implementation of the unsupervised PBSMT and NMT models presented in Phrase-Bas
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au
Sequence-to-Sequence Framework in PyTorch
nmtpytorch allows training of various end-to-end neural architectures including but not limited to neural machine translation, image captioning and au
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN.
Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU.
An easier way to build neural search on the cloud
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
A large-scale dataset of both raw MRI measurements and clinical MRI images
fastMRI is a collaborative research project from Facebook AI Research (FAIR) and NYU Langone Health to investigate the use of AI to make MRI scans faster. NYU Langone Health has released fully anonymized knee and brain MRI datasets that can be downloaded from the fastMRI dataset page. Publications associated with the fastMRI project can be found at the end of this README.
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee
SMPLpix: Neural Avatars from 3D Human Models
subject0_validation_poses.mp4 Left: SMPL-X human mesh registered with SMPLify-X, middle: SMPLpix render, right: ground truth video. SMPLpix: Neural Av
Generative Models for Graph-Based Protein Design
Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay
HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks
HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F
Learning Skeletal Articulations with Neural Blend Shapes
This repository provides an end-to-end library for automatic character rigging and blend shapes generation as well as a visualization tool. It is based on our work Learning Skeletal Articulations with Neural Blend Shapes that is published in SIGGRAPH 2021.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
A simple image/video to Desmos graph converter run locally
Desmos Bezier Renderer A simple image/video to Desmos graph converter run locally Sample Result Setup Install dependencies apt update apt install git
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform
An implementation of the paper "A Neural Algorithm of Artistic Style"
A Neural Algorithm of Artistic Style implementation - Neural Style Transfer This is an implementation of the research paper "A Neural Algorithm of Art
Unofficial & improved implementation of NeRF--: Neural Radiance Fields Without Known Camera Parameters
[Unofficial code-base] NeRF--: Neural Radiance Fields Without Known Camera Parameters [ Project | Paper | Official code base ] ⬅️ Thanks the original
This repository will contain the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields Project Page | Paper | Supplementary | Video | Slides | Blog | Talk If
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"
This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
"NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search".
NAS-Bench-301 This repository containts code for the paper: "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search". The
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,
Code and datasets for the paper "Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction" (RA-L, 2021)
Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction This is the code for the paper Combining E