3343 Repositories
Python deep-networks Libraries
A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".
RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo
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
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset
PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp
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
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
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
Sequence modeling benchmarks and temporal convolutional networks
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
Wind Speed Prediction using LSTMs in PyTorch
Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu
Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models.
Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized
High level network definitions with pre-trained weights in TensorFlow
TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.
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
Tensorforce: a TensorFlow library for applied reinforcement learning
Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,
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
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp
Train a deep learning net with OpenStreetMap features and satellite imagery.
DeepOSM Classify roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. DeepOSM can: Download a chunk of
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.
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research
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
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
DeepLab resnet v2 model in pytorch
pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from
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
Pytorch implementation of Value Iteration Networks (NIPS 2016 best paper)
VIN: Value Iteration Networks A quick thank you A few others have released amazing related work which helped inspire and improve my own implementation
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea
Image-to-Image Translation in PyTorch
CycleGAN and pix2pix in PyTorch New: Please check out contrastive-unpaired-translation (CUT), our new unpaired image-to-image translation model that e
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
Deep Reinforcement Learning with pytorch & visdom
Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A
Code for the paper "Adversarial Generator-Encoder Networks"
This repository contains code for the paper "Adversarial Generator-Encoder Networks" (AAAI'18) by Dmitry Ulyanov, Andrea Vedaldi, Victor Lempitsky. Pr
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
PyTorch implementation of Deformable Convolution
PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple
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
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran
PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.
VIN: Value Iteration Networks This is an implementation of Value Iteration Networks (VIN) in PyTorch to reproduce the results.(TensorFlow version) Key
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
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
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
Implementation of algorithms for continuous control (DDPG and NAF).
DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.
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
Implementation of Squeezenet in pytorch, pretrained models on Cifar 10 data to come
Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque
A PyTorch implementation of DenseNet.
A PyTorch Implementation of DenseNet This is a PyTorch implementation of the DenseNet-BC architecture as described in the paper Densely Connected Conv
Sequence to Sequence Models with PyTorch
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.
AnimeGAN A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. Randomly Generated Images The images are
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
3.8% and 18.3% on CIFAR-10 and CIFAR-100
Wide Residual Networks This code was used for experiments with Wide Residual Networks (BMVC 2016) http://arxiv.org/abs/1605.07146 by Sergey Zagoruyko
Wide Residual Networks (WideResNets) in PyTorch
Wide Residual Networks (WideResNets) in PyTorch WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than
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
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
Deep Q-Learning Network in pytorch (not actively maintained)
pytoch-dqn This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the followin
Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
DiscoGAN Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. Prerequisites Python 2.7
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM
A PyTorch Implementation of Single Shot MultiBox Detector
SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragom
PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
pix2pix-pytorch PyTorch implementation of Image-to-Image Translation Using Conditional Adversarial Networks. Based on pix2pix by Phillip Isola et al.
Task-based end-to-end model learning in stochastic optimization
Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th
Time Delayed NN implemented in pytorch
Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN
Recurrent Variational Autoencoder that generates sequential data implemented with pytorch
Pytorch Recurrent Variational Autoencoder Model: This is the implementation of Samuel Bowman's Generating Sentences from a Continuous Space with Kim's
PyTorch implementation of the Value Iteration Networks (VIN) (NIPS '16 best paper)
Value Iteration Networks in PyTorch Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P. Value Iteration Networks. Neural Information Processing
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
Realtime Multi-Person Pose Estimation By Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh. Introduction Code repo for winning 2016 MSCOCO Keypoints Cha
a pytorch implementation of auto-punctuation learned character by character
Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult
Fast Scattering Transform with CuPy/PyTorch
Announcement 11/18 This package is no longer supported. We have now released kymatio: http://www.kymat.io/ , https://github.com/kymatio/kymatio which
This implements one of result networks from Large-scale evolution of image classifiers
Exotic structured image classifier This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al. Req
Official DGL implementation of "Rethinking High-order Graph Convolutional Networks"
SE Aggregation This is the implementation for Rethinking High-order Graph Convolutional Networks. Here we show the codes for citation networks as an e
Official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT This repository is the official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification. ArXiv If
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
Kornia is a open source differentiable computer vision library for PyTorch.
Open Source Differentiable Computer Vision Library
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer
Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer This repository contains the PyTorch code for Evo-ViT. This work proposes a slow-fas
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
Learning based AI for playing multi-round Koi-Koi hanafuda card games. Have fun.
Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI
💛 Code and Dataset for our EMNLP 2021 paper: "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes"
Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes Official PyTorch implementation and EmoCause evaluatio
[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning [MedIA or Arxiv] and [Demo] This repository pr
TorchX: A PyTorch Extension Library for More Efficient Deep Learning
TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T
It is a tool that looks for a specific username in social networks
It is a tool that looks for a specific username in social networks
Netwalk is a Python library to discover, parse, analyze and change Cisco switched networks
Netwalk is a Python library born out of a large remadiation project aimed at making network device discovery and management as fast and painless as possible.
A collection of SOTA Image Classification Models in PyTorch
A collection of SOTA Image Classification Models in PyTorch
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Abstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.
Learning Opinion Summarizers by Selecting Informative Reviews This repository contains the codebase and the dataset for the corresponding EMNLP 2021
A program to recognize fruits on pictures or videos using yolov5
Yolov5 Fruits Detector Requirements Either Linux or Windows. We recommend Linux for better performance. Python 3.6+ and PyTorch 1.7+. Installation To
Vehicle Detection Using Deep Learning and YOLO Algorithm
VehicleDetection Vehicle Detection Using Deep Learning and YOLO Algorithm Dataset take or find vehicle images for create a special dataset for fine-tu
Implementation of a Transformer, but completely in Triton
Transformer in Triton (wip) Implementation of a Transformer, but completely in Triton. I'm completely new to lower-level neural net code, so this repo
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
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.
Standard implementations of FedLab and its provided benchmarks.
FedLab-benchmarks This repo contains standard implementations of FedLab and its provided benchmarks. Currently, following algorithms or benchrmarks ar
Implementation of Hierarchical Transformer Memory (HTM) for Pytorch
Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si
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.
Learn how to responsibly deliver value with ML.
Made With ML Applied ML · MLOps · Production Join 30K+ developers in learning how to responsibly deliver value with ML. 🔥 Among the top MLOps reposit
[ICCV2021] Official code for "Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition"
CTR-GCN This repo is the official implementation for Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition. The pap
Curvlearn, a Tensorflow based non-Euclidean deep learning framework.
English | 简体中文 Why Non-Euclidean Geometry Considering these simple graph structures shown below. Nodes with same color has 2-hop distance whereas 1-ho
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection Code for our Paper DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Obje
MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks.
MVGCN MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks. Developer: Fu Hait
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.
GNPy: Optical Route Planning and DWDM Network Optimization
GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks
Official implementation of Deep Burst Super-Resolution
Deep-Burst-SR Official implementation of Deep Burst Super-Resolution Publication: Deep Burst Super-Resolution. Goutam Bhat, Martin Danelljan, Luc Van
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation The code of: Cross-Image Region Mining with Region Proto
A Deep Reinforcement Learning Framework for Stock Market Trading
DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap
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.
Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".
StableNet StableNet is a deep stable learning method for out-of-distribution generalization. This is the official repo for CVPR21 paper "Deep Stable L
A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling" (ICCV 2021)
Manifold Matching via Deep Metric Learning for Generative Modeling A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generat