3100 Repositories
Python pytorch-gan Libraries
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
NeRF-pytorch NeRF (Neural Radiance Fields) is a method that achieves state-of-the-art results for synthesizing novel views of complex scenes. Here are
Bald-to-Hairy Translation Using CycleGAN
GANiry: Bald-to-Hairy Translation Using CycleGAN Official PyTorch implementation of GANiry. GANiry: Bald-to-Hairy Translation Using CycleGAN, Fidan Sa
[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax
[NeurIPS 2021] Galerkin Transformer: linear attention without softmax Summary A non-numerical analyst oriented explanation on Toward Data Science abou
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd
Google and Stanford University released a new pre-trained model called ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants. For further accelerating the research of the Chinese pre-trained model, the Joint Laboratory of HIT and iFLYTEK Research (HFL) has released the Chinese ELECTRA models based on the official code of ELECTRA. ELECTRA-small could reach similar or even higher scores on several NLP tasks with only 1/10 parameters compared to BERT and its variants.
Transfer-Learn is an open-source and well-documented library for Transfer Learning.
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
Trying to understand alias-free-gan.
alias-free-gan-explanation Trying to understand alias-free-gan in my own way. [Chinese Version 中文版本] CC-BY-4.0 License. Tzu-Heng Lin motivation of thi
A code copied from google-research which named motion-imitation was rewrited with PyTorch
motor-system Introduction A code copied from google-research which named motion-imitation was rewrited with PyTorch. More details can get from this pr
Pytorch implementation of VAEs for heterogeneous likelihoods.
Heterogeneous VAEs Beware: This repository is under construction 🛠️ Pytorch implementation of different VAE models to model heterogeneous data. Here,
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.
Dense matching library based on PyTorch
Dense Matching A general dense matching library based on PyTorch. For any questions, issues or recommendations, please contact Prune at prune.truong@v
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021) Jiaxi Jiang, Kai Zhang, Radu Timofte Computer Vision Lab, ETH Zurich, Switzerland 🔥
Pytorch implementation of the unsupervised object discovery method LOST.
LOST Pytorch implementation of the unsupervised object discovery method LOST. More details can be found in the paper: Localizing Objects with Self-Sup
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.
Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)
Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)
CLIPort: What and Where Pathways for Robotic Manipulation
CLIPort CLIPort: What and Where Pathways for Robotic Manipulation Mohit Shridhar, Lucas Manuelli, Dieter Fox CoRL 2021 CLIPort is an end-to-end imitat
Exploring Relational Context for Multi-Task Dense Prediction [ICCV 2021]
Adaptive Task-Relational Context (ATRC) This repository provides source code for the ICCV 2021 paper Exploring Relational Context for Multi-Task Dense
Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”
VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto
Tutel MoE: An Optimized Mixture-of-Experts Implementation
Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho
Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images (ICCV 2021)
Table of Content Introduction Getting Started Datasets Installation Experiments Training & Testing Pretrained models Texture fine-tuning Demo Toward R
Reinforcement learning framework and algorithms implemented in PyTorch.
Reinforcement learning framework and algorithms implemented in PyTorch.
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their
A PyTorch implementation of SlowFast based on ICCV 2019 paper "SlowFast Networks for Video Recognition"
SlowFast A PyTorch implementation of SlowFast based on ICCV 2019 paper SlowFast Networks for Video Recognition. Requirements Anaconda PyTorch conda in
A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.
A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models tabular data.
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System
Deep Face Recognition in PyTorch
Face Recognition in PyTorch By Alexey Gruzdev and Vladislav Sovrasov Introduction A repository for different experimental Face Recognition models such
a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch
pytorch-spynet This is a personal reimplementation of SPyNet [1] using PyTorch. Should you be making use of this work, please cite the paper according
GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]
GANimation: Anatomically-aware Facial Animation from a Single Image [Project] [Paper] Official implementation of GANimation. In this work we introduce
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Differentiable architecture search for convolutional and recurrent networks
Differentiable Architecture Search Code accompanying the paper DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang. arX
A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)
EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor
PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
Maximum Entropy Generators for Energy-Based Models All experiments have tensorboard visualizations for samples / density / train curves etc. To run th
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more
Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)
Large-Scale Long-Tailed Recognition in an Open World [Project] [Paper] [Blog] Overview Open Long-Tailed Recognition (OLTR) is the author's re-implemen
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)
Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3
PyTorch code to run synthetic experiments.
Code repository for Invariant Risk Minimization Source code for the paper: @article{InvariantRiskMinimization, title={Invariant Risk Minimization}
An inofficial PyTorch implementation of PREDATOR based on KPConv.
PREDATOR: Registration of 3D Point Clouds with Low Overlap An inofficial PyTorch implementation of PREDATOR based on KPConv. The code has been tested
(ICCV 2021) Official code of "Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing."
Dressing in Order (DiOr) 👚 [Paper] 👖 [Webpage] 👗 [Running this code] The official implementation of "Dressing in Order: Recurrent Person Image Gene
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019
PoseNet of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image" Introduction This repo is official Py
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar
This repo is official PyTorch implementation of MobileHumanPose: Toward real-time 3D human pose estimation in mobile devices(CVPRW 2021).
Github Code of "MobileHumanPose: Toward real-time 3D human pose estimation in mobile devices" Introduction This repo is official PyTorch implementatio
Torch Containers simplified in PyTorch
pytorch-containers This repository aims to help former Torchies more seamlessly transition to the "Containerless" world of PyTorch by providing a list
simple generative adversarial network (GAN) using PyTorch
Generative Adversarial Networks (GANs) in PyTorch Running Run the sample code by typing: ./gan_pytorch.py ...and you'll train two nets to battle it o
ConvNet training using pytorch
Convolutional networks using PyTorch This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition Currently
Some example scripts on pytorch
pytorch-practice Some example scripts on pytorch CONLL 2000 Chunking task Uses BiLSTM CRF loss with char CNN embeddings. To run use: cd data/conll2000
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P
PyTorch tutorials and best practices.
Effective PyTorch Table of Contents Part I: PyTorch Fundamentals PyTorch basics Encapsulate your model with Modules Broadcasting the good and the ugly
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
DeepNLP-models-Pytorch Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning) This is not for Pytorch be
Simple PyTorch Tutorials Zero to ALL!
PyTorchZeroToAll Quick 3~4 day lecture materials for HKUST students. Video Lectures: (RNN TBA) Youtube Bilibili Slides Lecture Slides @GoogleDrive If
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
PyTorch Tutorial for Deep Learning Researchers
This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less
An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
Table of Contents: Introduction to Torch's Tensor Library Computation Graphs and Automatic Differentiation Deep Learning Building Blocks: Affine maps,
Minimal tutorials for PyTorch
Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials. Tensor multiplication Linear Regression Logistic Regression Neural Network
Simple examples to introduce PyTorch
This repository introduces the fundamental concepts of PyTorch through self-contained examples. At its core, PyTorch provides two main features: An n-
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone OS (Compiler)\LibTorch 1.9.0 macOS (clang 10.0, 11.0, 12.0) Linux (gcc 8, 9, 10, 11) Windows (msv
Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.
Deep Learning Materials by Deep Learning Wizard Start Learning Now Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet fr
Deep Learning (with PyTorch)
Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.
D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Book website | STAT 157 Course at UC Berkeley | Latest version
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
PyTorch Examples WARNING: if you fork this repo, github actions will run daily on it. To disable this, go to /examples/settings/actions and Disable Ac
PyTorch tutorials.
PyTorch Tutorials All the tutorials are now presented as sphinx style documentation at: https://pytorch.org/tutorials Contributing We use sphinx-galle
pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
Soft-Decision-Tree Soft-Decision-Tree is the pytorch implementation of Distilling a Neural Network Into a Soft Decision Tree, paper recently published
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Neural-Backed Decision Trees · Site · Paper · Blog · Video Alvin Wan, *Lisa Dunlap, *Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah
Pytorch Feature Map Extractor
MapExtrackt Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can ide
Quickly and easily create / train a custom DeepDream model
Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat
Lucid library adapted for PyTorch
Lucent PyTorch + Lucid = Lucent The wonderful Lucid library adapted for the wonderful PyTorch! Lucent is not affiliated with Lucid or OpenAI's Clarity
Visualization toolkit for neural networks in PyTorch! Demo --
FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The
PyTorch implementation of DeepDream algorithm
neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br
Pytorch implementation of convolutional neural network visualization techniques
Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
Implementation of the Remixer Block from the Remixer paper, in Pytorch
Remixer - Pytorch Implementation of the Remixer Block from the Remixer paper, in Pytorch. It claims that substituting the feedforwards in transformers
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System
Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset
Reference-Based-Sketch-Image-Colorization-ImageNet This is a PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization usin
Unofficial Implementation of Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration
Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration This repo contains only model Implementation of Zero-Shot Text-to-Speech for Text
A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.
A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.
ilpyt: imitation learning library with modular, baseline implementations in Pytorch
ilpyt The imitation learning toolbox (ilpyt) contains modular implementations of common deep imitation learning algorithms in PyTorch, with unified in
A Closer Look at Structured Pruning for Neural Network Compression
A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w
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
Official implementations of EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis.
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin
Distiller is an open-source Python package for neural network compression research.
Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres
A PyTorch implementation of Learning to learn by gradient descent by gradient descent
Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST
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
A PyTorch implementation of L-BFGS.
PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?
Riemannian Adaptive Optimization Methods with pytorch optim
geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur
lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch
lookahead optimizer for pytorch PyTorch implement of Lookahead Optimizer: k steps forward, 1 step back Usage: base_opt = torch.optim.Adam(model.parame
functorch is a prototype of JAX-like composable function transforms for PyTorch.
functorch is a prototype of JAX-like composable function transforms for PyTorch.
docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
GluonMM is a library of transformer models for computer vision and multi-modality research
GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon Research.
Pytorch Geometric Tutorials
Pytorch Geometric Tutorials
Bunch of optimizer implementations in PyTorch
Bunch of optimizer implementations in PyTorch
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]
Code and data form the paper BERT Got a Date: Introducing Transformers to Temporal Tagging
BERT Got a Date: Introducing Transformers to Temporal Tagging Satya Almasian*, Dennis Aumiller*, and Michael Gertz Heidelberg University Contact us vi