1787 Repositories
Python neural-radiance-fields Libraries
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing
TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
The VeriNet toolkit for verification of neural networks
VeriNet The VeriNet toolkit is a state-of-the-art sound and complete symbolic interval propagation based toolkit for verification of neural networks.
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"
Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.
An experimental technique for efficiently exploring neural architectures.
SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit
An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"
Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional
Unofficial implementation of One-Shot Free-View Neural Talking Head Synthesis
face-vid2vid Usage Dataset Preparation cd datasets wget https://yt-dl.org/downloads/latest/youtube-dl -O youtube-dl chmod a+rx youtube-dl python load_
Search and filter videos based on objects that appear in them using convolutional neural networks
Thingscoop: Utility for searching and filtering videos based on their content Description Thingscoop is a command-line utility for analyzing videos se
Neural machine translation between the writings of Shakespeare and modern English using TensorFlow
Shakespeare translations using TensorFlow This is an example of using the new Google's TensorFlow library on monolingual translation going from modern
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Pretty Tensor - Fluent Neural Networks in TensorFlow
Pretty Tensor provides a high level builder API for TensorFlow. It provides thin wrappers on Tensors so that you can easily build multi-layer neural networks.
A best practice for tensorflow project template architecture.
A best practice for tensorflow project template architecture.
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
Deep-Leafsnap Convolutional Neural Networks have become largely popular in image tasks such as image classification recently largely due to to Krizhev
Tree LSTM implementation in PyTorch
Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If
Pytorch tutorials for Neural Style transfert
PyTorch Tutorials This tutorial is no longer maintained. Please use the official version: https://pytorch.org/tutorials/advanced/neural_style_tutorial
Fast Neural Style for Image Style Transform by Pytorch
FastNeuralStyle by Pytorch Fast Neural Style for Image Style Transform by Pytorch This is famous Fast Neural Style of Paper Perceptual Losses for Real
Implementation of Neural Style Transfer in Pytorch
PytorchNeuralStyleTransfer Code to run Neural Style Transfer from our paper Image Style Transfer Using Convolutional Neural Networks. Also includes co
pytorch implementation of fast-neural-style
fast-neural-style 🌇 🚀 NOTICE: This codebase is no longer maintained, please use the codebase from pytorch examples repository available at pytorch/e
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Pytorch implementation of DeepMind's differentiable neural computer paper.
DNC pytorch This is a Pytorch implementation of DeepMind's Differentiable Neural Computer (DNC) architecture introduced in their recent Nature paper:
Highway networks implemented in PyTorch.
PyTorch Highway Networks Highway networks implemented in PyTorch. Just the MNIST example from PyTorch hacked to work with Highway layers. Todo Make th
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
Neural network models for joint POS tagging and dependency parsing (CoNLL 2017-2018)
Neural Network Models for Joint POS Tagging and Dependency Parsing Implementations of joint models for POS tagging and dependency parsing, as describe
Kornia is a open source differentiable computer vision library for PyTorch.
Open Source Differentiable Computer Vision Library
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network
The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"
The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering"
This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction".
TreePartNet This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction". Depende
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
Collection of admin fields and decorators to help to create computed or custom fields more friendly and easy way
django-admin-easy Collection of admin fields, decorators and mixin to help to create computed or custom fields more friendly and easy way Installation
Must-read Papers on Physics-Informed Neural Networks.
PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
PennyLane is a cross-platform Python library for differentiable programming of quantum computers.
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Amplitude-Phase Recombination (ICCV'21) Official PyTorch implementation of "Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neur
G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
Single Node Injection Attack against Graph Neural Networks This repository is our Pytorch implementation of our paper: Single Node Injection Attack ag
neural image generation
pixray Pixray is an image generation system. It combines previous ideas including: Perception Engines which uses image augmentation and iteratively op
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications.
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications.
Face Mask Detection is a project to determine whether someone is wearing mask or not, using deep neural network.
face-mask-detection Face Mask Detection is a project to determine whether someone is wearing mask or not, using deep neural network. It contains 3 scr
Classifying audio using Wavelet transform and deep learning
Audio Classification using Wavelet Transform and Deep Learning A step-by-step tutorial to classify audio signals using continuous wavelet transform (C
Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV
Realtime Face Anti-Spoofing Detection 🤖 Realtime Face Anti Spoofing Detection with Face Detector to detect real and fake faces Please star this repo
This is the code for "HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields".
HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields This is the code for "HyperNeRF: A Higher-Dimensional
Unofficial pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing"
One-Shot Free-View Neural Talking Head Synthesis Unofficial pytorch implementation of paper "One-Shot Free-View Neural Talking-Head Synthesis for Vide
CMT: Convolutional Neural Networks Meet Vision Transformers
CMT: Convolutional Neural Networks Meet Vision Transformers [arxiv] 1. Introduction This repo is the CMT model which impelement with pytorch, no refer
PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation
PocketNet This is the official repository of the paper: PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and M
TorchIO is a Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.
codes for "Scheduled Sampling Based on Decoding Steps for Neural Machine Translation" (long paper of EMNLP-2022)
Scheduled Sampling Based on Decoding Steps for Neural Machine Translation (EMNLP-2021 main conference) Contents Overview Background Quick to Use Furth
Prototype for Baby Action Detection and Classification
Baby Action Detection Table of Contents About Install Run Predictions Demo About An attempt to harness the power of Deep Learning to come up with a so
Bayesian Neural Networks in PyTorch
We present the new scheme to compute Monte Carlo estimator in Bayesian VI settings with almost no memory cost in GPU, regardles of the number of sampl
Code and data for the EMNLP 2021 paper "Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts". Coming soon!
ToxiChat Code and data for the EMNLP 2021 paper "Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts". Install depen
SummerTime - Text Summarization Toolkit for Non-experts
A library to help users choose appropriate summarization tools based on their specific tasks or needs. Includes models, evaluation metrics, and datasets.
[ICCV 2021 Oral] NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
NerfingMVS Project Page | Paper | Video | Data NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Yi Wei, Shaohui
TAPEX: Table Pre-training via Learning a Neural SQL Executor
TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE
[ICCV21] Self-Calibrating Neural Radiance Fields
Self-Calibrating Neural Radiance Fields, ICCV, 2021 Project Page | Paper | Video Author Information Yoonwoo Jeong [Google Scholar] Seokjun Ahn [Google
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
(ICCV'21) Official PyTorch implementation of Relational Embedding for Few-Shot Classification
Relational Embedding for Few-Shot Classification (ICCV 2021) Dahyun Kang, Heeseung Kwon, Juhong Min, Minsu Cho [paper], [project hompage] We propose t
ManipNet: Neural Manipulation Synthesis with a Hand-Object Spatial Representation - SIGGRAPH 2021
ManipNet: Neural Manipulation Synthesis with a Hand-Object Spatial Representation - SIGGRAPH 2021 Dataset Code Demos Authors: He Zhang, Yuting Ye, Tak
PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation.
PyNIF3D is an open-source PyTorch-based library for research on neural implicit functions (NIF)-based 3D geometry representation. It aims to accelerate research by providing a modular design that allows for easy extension and combination of NIF-related components, as well as readily available paper implementations and dataset loaders.
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ
Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
disclaimer: this code is modified from pytorch-tutorial Image classification with synthetic gradient in Pytorch I implement the Decoupled Neural Inter
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet
Neural Message Passing for Computer Vision
Neural Message Passing for Quantum Chemistry Implementation of different models of Neural Networks on graphs as explained in the article proposed by G
Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks)
Pytorch implementation of Relational Networks - A simple neural network module for relational reasoning Implemented & tested on Sort-of-CLEVR task. So
Principled Detection of Out-of-Distribution Examples in Neural Networks
ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time"
forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
samplernn-pytorch A PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. It's based on the reference implem
An experimental technique for efficiently exploring neural architectures.
SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit
Find target hash collisions for Apple's NeuralHash perceptual hash function.💣
neural-hash-collider Find target hash collisions for Apple's NeuralHash perceptual hash function. For example, starting from a picture of this cat, we
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''
The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Deep learning for spiking neural networks
A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even
BARF: Bundle-Adjusting Neural Radiance Fields 🤮 (ICCV 2021 oral)
BARF 🤮 : Bundle-Adjusting Neural Radiance Fields Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey IEEE International Conference on Comp
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21
MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen
[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving
NEAT: Neural Attention Fields for End-to-End Autonomous Driving Paper | Supplementary | Video | Poster | Blog This repository is for the ICCV 2021 pap
The official repo for CVPR2021——ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search.
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search [paper] Introduction This is the official implementation of ViPNAS: Efficient V
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"
This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.
Neural Turing Machines (NTM) - PyTorch Implementation
PyTorch Neural Turing Machine (NTM) PyTorch implementation of Neural Turing Machines (NTM). An NTM is a memory augumented neural network (attached to
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.
YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret
An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.
简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型,分别是SimpleCNN和MiniXception。利用 imdb_crop
The official implementation of the IEEE S&P`22 paper "SoK: How Robust is Deep Neural Network Image Classification Watermarking".
Watermark-Robustness-Toolbox - Official PyTorch Implementation This repository contains the official PyTorch implementation of the following paper to
QTool: A Low-bit Quantization Toolbox for Deep Neural Networks in Computer Vision
This project provides abundant choices of quantization strategies (such as the quantization algorithms, training schedules and empirical tricks) for quantizing the deep neural networks into low-bit counterparts.
Guesslang detects the programming language of a given source code
Detect the programming language of a source code
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)
CM-NAS Official Pytorch code of paper CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification in ICCV2021. Vis