2754 Repositories
Python self-normalizing-neural-networks Libraries
pulse2percept: A Python-based simulation framework for bionic vision
pulse2percept: A Python-based simulation framework for bionic vision Retinal degenerative diseases such as retinitis pigmentosa and macular degenerati
PN-Net a neural field-based framework for depth estimation from single-view RGB images.
PN-Net We present a neural field-based framework for depth estimation from single-view RGB images. Rather than representing a 2D depth map as a single
Unsupervised Image Generation with Infinite Generative Adversarial Networks
Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da
Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021
Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
GUI for a Vocal Remover that uses Deep Neural Networks.
GUI for a Vocal Remover that uses Deep Neural Networks.
SoGCN: Second-Order Graph Convolutional Networks
SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py
Analysis of rationale selection in neural rationale models
Neural Rationale Interpretability Analysis We analyze the neural rationale models proposed by Lei et al. (2016) and Bastings et al. (2019), as impleme
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias
Implementation of paper "Graph Condensation for Graph Neural Networks"
GCond A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks" Code will be released soon. Stay tuned :) Abstract We propose a
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Training Efficiency We show the training efficiency of our DSLP model b
Progressive Image Deraining Networks: A Better and Simpler Baseline
Progressive Image Deraining Networks: A Better and Simpler Baseline [arxiv] [pdf] [supp] Introduction This paper provides a better and simpler baselin
Image Super-Resolution by Neural Texture Transfer
SRNTT: Image Super-Resolution by Neural Texture Transfer Tensorflow implementation of the paper Image Super-Resolution by Neural Texture Transfer acce
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.
EDVR has been merged into BasicSR. This GitHub repo is a mirror of BasicSR. Recommend to use BasicSR, and open issues, pull requests, etc in BasicSR.
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
Implementation of Graph Convolutional Networks in TensorFlow
Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)
Intro This repository contains code to generate data and reproduce experiments from our NeurIPS 2019 paper: Boris Knyazev, Graham W. Taylor, Mohamed R
Graph Convolutional Networks for Temporal Action Localization (ICCV2019)
Graph Convolutional Networks for Temporal Action Localization This repo holds the codes and models for the PGCN framework presented on ICCV 2019 Graph
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
Graph Attention Networks
GAT Graph Attention Networks (Veličković et al., ICLR 2018): https://arxiv.org/abs/1710.10903 GAT layer t-SNE + Attention coefficients on Cora Overvie
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte
The code is an implementation of Feedback Convolutional Neural Network for Visual Localization and Segmentation.
Feedback Convolutional Neural Network for Visual Localization and Segmentation The code is an implementation of Feedback Convolutional Neural Network
The repo of Feedback Networks, CVPR17
Feedback Networks http://feedbacknet.stanford.edu/ Paper: Feedback Networks, CVPR 2017. Amir R. Zamir*,Te-Lin Wu*, Lin Sun, William B. Shen, Bertram E
Deep Residual Networks with 1K Layers
Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc
Bittensor - an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence
At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.
Solutions of Reinforcement Learning 2nd Edition
Solutions of Reinforcement Learning, An Introduction
PyTorch implementation of "LayoutTransformer: Layout Generation and Completion with Self-attention"
PyTorch implementation of "LayoutTransformer: Layout Generation and Completion with Self-attention" to appear in ICCV 2021
A JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short.
BraVe This is a JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short. The model provided in this package wa
SynNet - synthetic tree generation using neural networks
SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
Quantum-enhanced transformer neural network
Example of a Quantum-enhanced transformer neural network Get the code: git clone https://github.com/rdisipio/qtransformer.git cd qtransformer Create
Semi-Supervised Signed Clustering Graph Neural Network (and Implementation of Some Spectral Methods)
SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on
This is an official pytorch implementation of Fast Fourier Convolution.
Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021)
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
The self-supervised goal reaching benchmark introduced in Discovering and Achieving Goals via World Models
Lexa-Benchmark Codebase for the self-supervised goal reaching benchmark introduced in 'Discovering and Achieving Goals via World Models'. Setup Create
PyTorch implementation of PP-LCNet: A Lightweight CPU Convolutional Neural Network
PyTorch implementation of PP-LCNet Reproduction of PP-LCNet architecture as described in PP-LCNet: A Lightweight CPU Convolutional Neural Network by C
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection, AAAI 2021.
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection This repository is an official implementation of the AAAI 2021 paper Co-mi
Neural text generators like the GPT models promise a general-purpose means of manipulating texts.
Boolean Prompting for Neural Text Generators Neural text generators like the GPT models promise a general-purpose means of manipulating texts. These m
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
Neural Motion Learner With Python
Neural Motion Learner Introduction This work is to extract skeletal structure from volumetric observations and to learn motion dynamics from the detec
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning This repository is the official implementation of CARE.
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).
DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a
Repo for EchoVPR: Echo State Networks for Visual Place Recognition
EchoVPR Repo for EchoVPR: Echo State Networks for Visual Place Recognition Currently under development Dirs: data: pre-collected hidden representation
Code for "Understanding Pooling in Graph Neural Networks"
Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install
Instance-based label smoothing for improving deep neural networks generalization and calibration
Instance-based Label Smoothing for Neural Networks Pytorch Implementation of the algorithm. This repository includes a new proposed method for instanc
Simple (but Strong) Baselines for POMDPs
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific
Disturbing Target Values for Neural Network regularization: attacking the loss layer to prevent overfitting
Disturbing Target Values for Neural Network regularization: attacking the loss layer to prevent overfitting 1. Classification Task PyTorch implementat
Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.
Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D
PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"
PASS - Official PyTorch Implementation [CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning Fei Zhu, Xu-Yao Zhang, Chu
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Style-based Neural Drum Synthesis with GAN inversion
Style-based Drum Synthesis with GAN Inversion Demo TensorFlow implementation of a style-based version of the adversarial drum synth (ADS) from the pap
Code for Understanding Pooling in Graph Neural Networks
Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install
A MassDM selfbot which is working in 2021
mass-dm-discord - Little preview of the Logger and the Spammer Features Logging User IDS Sending DMs to the logged IDs Blacklist IDs (add the ID of th
A self-hosted Discord music bot.
Cassette A self-hosted Discord music bot. Requirements py-cord pynacl pytube Setup Intended to be hosted on Heroku. Fork or clone this repo. Create a
[ICCV'21] UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction Project Page | Paper | Supplementary | Video This reposit
Official PyTorch implementation of "AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks"
AASIST This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in 'AASIST: Audio Anti-Spoofing
The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
SubTab: Author: Talip Ucar ([email protected]) The official implementation of the paper, SubTab: Subsetting Features of Tabular Data for Self-Supervis
FAST-RIR: FAST NEURAL DIFFUSE ROOM IMPULSE RESPONSE GENERATOR
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
[ICCV21] Code for RetrievalFuse: Neural 3D Scene Reconstruction with a Database
RetrievalFuse Paper | Project Page | Video RetrievalFuse: Neural 3D Scene Reconstruction with a Database Yawar Siddiqui, Justus Thies, Fangchang Ma, Q
Azure Neural Speech Service TTS
Written in Python using the Azure Speech SDK. App.py provides an easy way to create an Text-To-Speech request to Azure Speech and download the wav file.
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation
Permute Me Softly: Learning Soft Permutations for Graph Representations
Permute Me Softly: Learning Soft Permutations for Graph Representations
Hypercomplex Neural Networks with PyTorch
HyperNets Hypercomplex Neural Networks with PyTorch: this repository would be a container for hypercomplex neural network modules to facilitate resear
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network
Speech Separation Using an Asynchronous Fully Recurrent Convolutional Neural Network This repository is the official implementation of Speech Separati
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech
PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors
-IEEE-TIM-2021-1-Shallow-CNN-for-HAR [IEEE TIM 2021-1] Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors All
Neural network for recognizing the gender of people in photos
Neural Network For Gender Recognition How to test it? Install requirements.txt file using pip install -r requirements.txt command Run nn.py using pyth
A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features
A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features
A geometric deep learning pipeline for predicting protein interface contacts.
A geometric deep learning pipeline for predicting protein interface contacts.
A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures
A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures
A Robust Avatar Generator with a huge number of templates
CoolAvatars Welcome to this repository of CoolAvatars. Using this project, you can generate cool avatars not only from the samples present in my image
HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.
HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob
ChessCoach is a neural network-based chess engine capable of natural-language commentary.
ChessCoach is a neural network-based chess engine capable of natural-language commentary.
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021)
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021) This repository contains the code
Official Implementation of Neural Splines
Neural Splines: Fitting 3D Surfaces with Inifinitely-Wide Neural Networks This repository contains the official implementation of the CVPR 2021 (Oral)
Video Autoencoder: self-supervised disentanglement of 3D structure and motion
Video Autoencoder: self-supervised disentanglement of 3D structure and motion This repository contains the code (in PyTorch) for the model introduced
PortaSpeech - PyTorch Implementation
PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor
A library for performing coverage guided fuzzing of neural networks
TensorFuzz: Coverage Guided Fuzzing for Neural Networks This repository contains a library for performing coverage guided fuzzing of neural networks,
A simple but useful Discord Selfbot with essential features, made with discord.py-self.
Discord Selfbot Xyno Discord Selfbot Xyno is a simple but useful selfbot for Discord. It has currently limited useful features but it will be updated
This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)
Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation (TESKD) By Zheng Li[1,4], Xiang Li[2], Lingfeng Yang[2,4], Jian Yang[2], Zh
TensorFlow implementation of "Variational Inference with Normalizing Flows"
[TensorFlow 2] Variational Inference with Normalizing Flows TensorFlow implementation of "Variational Inference with Normalizing Flows" [1] Concept Co
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang