Python Tensor-networks Resources

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.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

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

GCN-LPA This repository is the implementation of GCN-LPA (arXiv): Unifying Graph Convolutional Neural Networks and Label Propagation Hongwei Wang, Jur

Editable neural networks A supplementary code for Editable Neural Networks, an ICLR 2020 submission by Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Py

NR-GAN: Noise Robust Generative Adversarial Networks (CVPR 2020) This repository provides PyTorch implementation for noise robust GAN (NR-GAN). NR-GAN

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

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.

Mixed supervision for surface-defect detection: from weakly to fully supervised learning [Computers in Industry 2021] Official PyTorch implementation

DeepFRI Deep functional residue identification Citing @article {Gligorijevic2019, author = {Gligorijevic, Vladimir and Renfrew, P. Douglas and Koscio

AngularGrad Optimizer This repository contains the oficial implementation for AngularGrad: A New Optimization Technique for Angular Convergence of Con

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".

BRIMs Bidirectional Recurrent Independent Mechanisms Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neura

Shapley Explanation Networks Implementation of the paper "Shapley Explanation Networks" at ICLR 2021. Note that this repo heavily uses the experimenta

LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian

Summary This is the code for the paper Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks by Yanxiang Wang, Xian Zh

Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr

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

Deep Networks from the Principle of Rate Reduction This repository is the official PyTorch implementation of the paper Deep Networks from the Principl

mlp-mixer-pytorch PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021) Usage import torch from mlp_mixer

OSCAR This repository contains the source code of our ICML 2021 paper How could Neural Networks understand Programs?. Environment Run following comman

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio

MevonAI - Speech Emotion Recognition

This is the code associated with the paper Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks, published at CVPR 2020.

DG-Font: Deformable Generative Networks for Unsupervised Font Generation The source code for 'DG-Font: Deformable Generative Networks for Unsupervised

The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys

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.

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 Molecular interaction networks are powerful resources for the discovery. While dee

HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction This is the code for the paper Combining E

GLOM PyTorch implementation of GLOM, Geoffrey Hinton's new idea that integrates concepts from neural fields, top-down-bottom-up processing, and attent

TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and GPT) or huge classes (millions). It has the same API design as PyTorch.

CorNet Correlation Networks for Extreme Multi-label Text Classification Prerequisites python==3.6.3 pytorch==1.2.0 torchgpipe==0.0.5 click==7.0 ruamel

Cockpit is a visual and statistical debugger specifically designed for deep learning!

Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc

This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

Profil3r is an OSINT tool that allows you to find potential profiles of a person on social networks, as well as their email addresses. This program also alerts you to the presence of a data leak for the found emails.

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

PyTorch for Semantic Segmentation This repository contains some models for semantic segmentation and the pipeline of training and testing models, impl

Submanifold Sparse Convolutional Networks This is the PyTorch library for training Submanifold Sparse Convolutional Networks. Spatial sparsity This li

Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F

QA-GNN: Question Answering using Language Models and Knowledge Graphs This repo provides the source code & data of our paper: QA-GNN: Reasoning with L

Try out deep learning models online on Google Colab

I-BERT: Integer-only BERT Quantization HuggingFace Implementation I-BERT is also available in the master branch of HuggingFace! Visit the following li

CondenseNetV2 This repository is the official Pytorch implementation for "CondenseNet V2: Sparse Feature Reactivation for Deep Networks" paper by Le Y

Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta

Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co

Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th

qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

OSMnet Tools for the extraction of OpenStreetMap (OSM) street network data. Intended to be used in tandem with Pandana and UrbanAccess libraries to ex

OSMnx OSMnx is a Python package that lets you download geospatial data from OpenStreetMap and model, project, visualize, and analyze real-world street

Automatic neural network visualizations generated in your browser!

PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021) This repo presents PyTorch implementation of M

ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement Recently, the power of unconditional image synthesis has significantly advanced th

TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I

Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-

Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks Abstract Facial expression recognition in video

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

A-CNN: Annularly Convolutional Neural Networks on Point Clouds Created by Artem Komarichev, Zichun Zhong, Jing Hua from Department of Computer Science

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Truly shift-invariant convolutional neural networks [Paper] Authors: Anadi Chaman and Ivan Dokmanić Convolutional neural networks were always assumed

Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

deep-significance: Easy and Better Significance Testing for Deep Neural Networks Contents ⁉️ Why 📥 Installation 🔖 Examples Intermezzo: Almost Stocha

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl

Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru

Tez: a simple pytorch trainer NOTE: Currently, we are not accepting any pull requests! All PRs will be closed. If you want a feature or something does

Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

README TabNet : Attentive Interpretable Tabular Learning This is a pyTorch implementation of Tabnet (Arik, S. O., & Pfister, T. (2019). TabNet: Attent

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

CuPy : A NumPy-compatible array library accelerated by CUDA Website | Docs | Install Guide | Tutorial | Examples | API Reference | Forum CuPy is an im

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

Open-L2O This repository establishes the first comprehensive benchmark efforts of existing learning to optimize (L2O) approaches on a number of proble