1368 Repositories
Python sum-product-networks Libraries
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
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
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 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
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
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.
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
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
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
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
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.
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
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.
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.
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)
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
Ebay Webscraper for Getting Average Product Price
Ebay-Webscraper-for-Getting-Average-Product-Price The code in this repo is used to determine the average price of an item on Ebay given a valid search
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 Multi-scale Matching Networks for Semantic Correspondence, ICCV
MMNet This repo is the official implementation of ICCV 2021 paper "Multi-scale Matching Networks for Semantic Correspondence.". Pre-requisite conda cr
[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
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
An Implementation of SiameseRPN with Feature Pyramid Networks
SiameseRPN with FPN This project is mainly based on HelloRicky123/Siamese-RPN. What I've done is just add a Feature Pyramid Network method to the orig
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
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.
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
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.
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J
(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
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation
Code for "On the Effects of Batch and Weight Normalization in Generative Adversarial Networks"
Note: this repo has been discontinued, please check code for newer version of the paper here Weight Normalized GAN Code for the paper "On the Effects
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
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 [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
Temporal Segment Networks (TSN) in PyTorch
TSN-Pytorch We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation for TSN as well as oth
Oriented Response Networks, in CVPR 2017
Oriented Response Networks [Home] [Project] [Paper] [Supp] [Poster] Torch Implementation The torch branch contains: the official torch implementation
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 ''
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation
Code for the ICCV 2021 paper "Pixel Difference Networks for Efficient Edge Detection" (Oral).
Pixel Difference Convolution This repository contains the PyTorch implementation for "Pixel Difference Networks for Efficient Edge Detection" by Zhuo
[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
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction
SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python
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
Official repository for MixFaceNets: Extremely Efficient Face Recognition Networks
MixFaceNets This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks. (Accepted in IJCB2021) https://i
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
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
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.
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
Guesslang detects the programming language of a given source code
Detect the programming language of a source code
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
Generative Flow Networks
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Implementation for our paper, submitted to NeurIPS 2021 (also chec
Official PyTorch implementation of the paper: Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net
Ἀνατομή is a PyTorch library to analyze representation of neural networks
Ἀνατομή is a PyTorch library to analyze representation of neural networks
10th place solution for Google Smartphone Decimeter Challenge at kaggle.
Under refactoring 10th place solution for Google Smartphone Decimeter Challenge at kaggle. Google Smartphone Decimeter Challenge Global Navigation Sat
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN-v2 StackGAN-v1: Tensorflow implementation StackGAN-v1: Pytorch implementation Inception score evaluation Pytorch implementation for reproduci
Graph Convolutional Networks in PyTorch
Graph Convolutional Networks in PyTorch PyTorch implementation of Graph Convolutional Networks (GCNs) for semi-supervised classification [1]. For a hi
Learning and Building Convolutional Neural Networks using PyTorch
Image Classification Using Deep Learning Learning and Building Convolutional Neural Networks using PyTorch. Models, selected are based on number of ci
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE TGRS, 2021.
Graph Convolutional Networks for Hyperspectral Image Classification Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot T
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on
Code accompanying our paper Feature Learning in Infinite-Width Neural Networks
Empirical Experiments in "Feature Learning in Infinite-width Neural Networks" This repo contains code to replicate our experiments (Word2Vec, MAML) in
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
Vanilla and Prototypical Networks with Random Weights for image classification on Omniglot and mini-ImageNet. Made with Python3.
vanilla-rw-protonets-project Vanilla Prototypical Networks and PNs with Random Weights for image classification on Omniglot and mini-ImageNet. Made wi
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)
CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks Authors: Xiang Zhang ([email protected]), Marinka Zitnik (marinka@hms.
Sum-Product Probabilistic Language
Sum-Product Probabilistic Language SPPL is a probabilistic programming language that delivers exact solutions to a broad range of probabilistic infere
Official implementation of the paper ``Unifying Nonlocal Blocks for Neural Networks'' (ICCV'21)
Spectral Nonlocal Block Overview Official implementation of the paper: Unifying Nonlocal Blocks for Neural Networks (ICCV'21) Spectral View of Nonloca
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations
ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary
Amazon Scraper: A command-line tool for scraping Amazon product data
Amazon Product Scraper: 2021 Description A command-line tool for scraping Amazon product data to CSV or JSON format(s). Requirements Python 3 pip3 Ins
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",
DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L
Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin, Mike Wu, and Noah Goodman Paper link: https://arxiv.org/abs/2
Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated
This is project is the implementation of the DeepShift: Towards Multiplication-Less Neural Networks paper
DeepShift This is project is the implementation of the DeepShift: Towards Multiplication-Less Neural Networks paper, that aims to replace multiplicati
A library for uncertainty representation and training in neural networks.
Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks)
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks) This repository contains a PyTorch implementation for the paper: Deep Pyra
A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer".
An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr
Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks"
HKD Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks" cifia-100 result The implementation of compared methods are ba
Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX.
Equinox Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX Equinox brings more power to your model building in JAX. Repr
Image Deblurring using Generative Adversarial Networks
DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo
Image restoration with neural networks but without learning.
Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s
Deep Learning Head Pose Estimation using PyTorch.
Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.