3915 Repositories
Python Value-Iteration-Networks-PyTorch Libraries
Liver segmentation using MONAI and pytorch
Machine Learning use case in the field of Healthcare. In this project MONAI and pytorch frameworks are used for 3D Liver segmentation.
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G
Face uncertainty quantification or estimation using PyTorch.
Face-uncertainty-pytorch This is a demo code of face uncertainty quantification or estimation using PyTorch. The uncertainty of face recognition is af
Mapping a variable-length sentence to a fixed-length vector using BERT model
Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc
Keras implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
This is code of book "Learn Deep Learning with PyTorch"
深度学习入门之PyTorch Learn Deep Learning with PyTorch 非常感谢您能够购买此书,这个github repository包含有深度学习入门之PyTorch的实例代码。由于本人水平有限,在写此书的时候参考了一些网上的资料,在这里对他们表示敬意。由于深度学习的技术在
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
A tiny, pedagogical neural network library with a pytorch-like API.
candl A tiny, pedagogical implementation of a neural network library with a pytorch-like API. The primary use of this library is for education. Use th
RGBD-Net - This repository contains a pytorch lightning implementation for the 3DV 2021 RGBD-Net paper.
[3DV 2021] We propose a new cascaded architecture for novel view synthesis, called RGBD-Net, which consists of two core components: a hierarchical depth regression network and a depth-aware generator network.
A Transformer Implementation that is easy to understand and customizable.
Simple Transformer I've written a series of articles on the transformer architecture and language models on Medium. This repository contains an implem
PyTorch implementation of Lip to Speech Synthesis with Visual Context Attentional GAN (NeurIPS2021)
Lip to Speech Synthesis with Visual Context Attentional GAN This repository contains the PyTorch implementation of the following paper: Lip to Speech
Unofficial PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution
PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].
Pytorch implementation of our method for regularizing nerual radiance fields for few-shot neural volume rendering.
InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Rendering Pytorch implementation of our method for regularizing nerual radiance fields f
Pytorch implementation of local motion and contrast prior driven deep network (MoCoPnet)
MoCoPnet: Exploring Local Motion and Contrast Priors for Infrared Small Target Super-Resolution Pytorch implementation of local motion and contrast pr
Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients
LSF-SAC Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy G
An Evaluation of Generative Adversarial Networks for Collaborative Filtering.
An Evaluation of Generative Adversarial Networks for Collaborative Filtering. This repository was developed by Fernando B. Pérez Maurera. Fernando is
Neural network pruning for finding a sparse computational model for controlling a biological motor task.
MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec
This is the Pytorch implementation of Progressive Attentional Manifold Alignment.
PAMA This is the Pytorch implementation of Progressive Attentional Manifold Alignment. Requirements python 3.6 pytorch 1.2.0+ PIL, numpy, matplotlib C
PyTorch implementation for STIN
STIN This repository contains PyTorch implementation for STIN. Abstract: In single-photon LiDAR, photon-efficient imaging captures the 3D structure of
Pytorch implementation of NEGEV method. Paper: "Negative Evidence Matters in Interpretable Histology Image Classification".
Pytorch 1.10.0 code for: Negative Evidence Matters in Interpretable Histology Image Classification (https://arxiv. org/abs/xxxx.xxxxx) Citation: @arti
A general framework for inferring CNNs efficiently. Reduce the inference latency of MobileNet-V3 by 1.3x on an iPhone XS Max without sacrificing accuracy.
GFNet-Pytorch (NeurIPS 2020) This repo contains the official code and pre-trained models for the glance and focus network (GFNet). Glance and Focus: a
Torchyolo - Yolov3 ve Yolov4 modellerin Pytorch uygulamasıdır
TORCHYOLO : Yolo Modellerin Pytorch Uygulaması Yapılacaklar: Yolov3 model.py ve
Exploration of BERT-based models on twitter sentiment classifications
twitter-sentiment-analysis Explore the relationship between twitter sentiment of Tesla and its stock price/return. Explore the effect of different BER
PyTorch implementation(s) of various ResNet models from Twitch streams.
pytorch-resnet-twitch PyTorch implementation(s) of various ResNet models from Twitch streams. Status: ResNet50 currently not working. Will update in n
A curated list for getting up to speed on crypto and decentralized networks
crypto reading list A curated list for getting up to speed on crypto and decentralized networks. The content on the toplevel page contains what we con
deep learning for image processing including classification and object-detection etc.
深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结,总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享,教学流程如下: 1)介绍网络的结构与创新点 2)使用Pytorch进行网络的搭建与训练 3)使用Te
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
Python package for Near Duplicate Video Detection (Perceptual Video Hashing) - Get a 64-bit comparable hash-value for any video.
The Python package for near duplicate video detection ⭐️ Introduction Videohash is a Python package for detecting near-duplicate videos (Perceptual Vi
The Qis|krypt⟩ is a software suite of protocols of quantum cryptography and quantum communications
The Qis|krypt⟩ is a software suite of protocols of quantum cryptography and quantum communications, as well, other protocols and algorithms, built using IBM’s open-source Software Development Kit for quantum computing Qiskit. ⚛️ 🔐
A High-Quality Real Time Upscaler for Anime Video
Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua
Pure python implementations of popular ML algorithms.
Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks
Official respository for "Band-limited Coordinate Networks for Multiscale Scene Representation"
BACON: Band-limited Coordinate Networks for Multiscale Scene Representation Project Page | Video | Paper Official PyTorch implementation of BACON. BAC
PyTorch implementaton of our CVPR 2021 paper "Bridging the Visual Gap: Wide-Range Image Blending"
Bridging the Visual Gap: Wide-Range Image Blending PyTorch implementaton of our CVPR 2021 paper "Bridging the Visual Gap: Wide-Range Image Blending".
Official PyTorch implementation of "The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation" (ICCV 21).
CenterGroup This the official implementation of our ICCV 2021 paper The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person P
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly
End-to-end Temporal Action Detection with Transformer. [Under review]
TadTR: End-to-end Temporal Action Detection with Transformer By Xiaolong Liu, Qimeng Wang, Yao Hu, Xu Tang, Song Bai, Xiang Bai. This repo holds the c
PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @
PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge"
FSGAN Here is the official PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge". This project achieve the translation between
This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation).
FlatGCN This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation, submitted to ICASSP2022). Req
A Simple Key-Value Data-store written in Python
mercury-db This is a File Based Key-Value Datastore that supports basic CRUD (Create, Read, Update, Delete) operations developed using Python. The dat
Deep Learning pipeline for motor-imagery classification.
BCI-ToolBox 1. Introduction BCI-ToolBox is deep learning pipeline for motor-imagery classification. This repo contains five models: ShallowConvNet, De
simple_pytorch_example project is a toy example of a python script that instantiates and trains a PyTorch neural network on the FashionMNIST dataset
simple_pytorch_example project is a toy example of a python script that instantiates and trains a PyTorch neural network on the FashionMNIST dataset
Neural-net-from-scratch - A simple Neural Network from scratch in Python using the Pymathrix library
A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt
Pytorch reimplementation of the Mixer (MLP-Mixer: An all-MLP Architecture for Vision)
MLP-Mixer Pytorch reimplementation of Google's repository for the MLP-Mixer (Not yet updated on the master branch) that was released with the paper ML
PyTorch GPU implementation of the ES-RNN model for time series forecasting
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm A GPU-enabled version of the hybrid ES-RNN model by Slawek et al that won the M4 time-series
Implementation of deep learning models for time series in PyTorch.
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Fully Convlutional Neural Networks for state-of-the-art time series classification
Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin
Deep Learning for Time Series Classification
Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re
U-Time: A Fully Convolutional Network for Time Series Segmentation
U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
PyTorch implementation of the REMIND method from our ECCV-2020 paper "REMIND Your Neural Network to Prevent Catastrophic Forgetting"
REMIND Your Neural Network to Prevent Catastrophic Forgetting This is a PyTorch implementation of the REMIND algorithm from our ECCV-2020 paper. An ar
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
PyTorch implementation of "Continual Learning with Deep Generative Replay", NIPS 2017
pytorch-deep-generative-replay PyTorch implementation of Continual Learning with Deep Generative Replay, NIPS 2017 Results Continual Learning on Permu
A PyTorch implementation of the continual learning experiments with deep neural networks
Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain
Bacon - Band-limited Coordinate Networks for Multiscale Scene Representation
BACON: Band-limited Coordinate Networks for Multiscale Scene Representation Proj
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
Adds timm pretrained backbone to pytorch's FasterRcnn model
timmFasterRcnn model_config.py - it returns the model,feat_sizes,output channel and the feat layer names, which is reqd by the Add_FPN.py file Add_FP
Implementation of Convolutional LSTM in PyTorch.
ConvLSTM_pytorch This file contains the implementation of Convolutional LSTM in PyTorch made by me and DavideA. We started from this implementation an
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers.
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.
PyTorch EO aims to make Deep Learning for Earth Observation data easy and accessible to real-world cases and research alike.
Pytorch EO Deep Learning for Earth Observation applications and research. 🚧 This project is in early development, so bugs and breaking changes are ex
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
Tutorials and implementations for "Self-normalizing networks"
Self-Normalizing Networks Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print). Vers
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Setup and customize deep learning environment in seconds.
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)
U-GAT-IT — Official TensorFlow Implementation (ICLR 2020) : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization fo
Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Semantic Segmentation".
Dual Path Learning for Domain Adaptation of Semantic Segmentation Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Sema
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)
FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation
A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.
Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization
FAC-Net Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization Linjiang Huang (CUHK), Liang Wang (CASIA), Hongsheng
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
Official implementation of MSR-GCN (ICCV 2021 paper)
MSR-GCN Official implementation of MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction (ICCV 2021 paper) [Paper] [Sup
PyTorch implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021)
MT-ORL: Multi-Task Occlusion Relationship Learning Official implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021) P
ALBERT-pytorch-implementation - ALBERT pytorch implementation
ALBERT-pytorch-implementation developing... 모델의 개념이해를 돕기 위한 구현물로 현재 변수명을 상세히 적었고
Various converters to convert value sets from CSV to JSON, etc.
ValueSet Converters Tools for converting value sets in different formats. Such as converting extensional value sets in CSV format to JSON format able
python 93% acc. CNN Dogs Vs Cats ( Pytorch )
English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于
Supporting code for short YouTube series Neural Networks Demystified.
Neural Networks Demystified Supporting iPython notebooks for the YouTube Series Neural Networks Demystified. I've included formulas, code, and the tex
Machine Learning Study 혼자 해보기
Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil
Code for the Lovász-Softmax loss (CVPR 2018)
The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks Maxim Berman, Amal Ranne
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
Do you want a RL agent nicely moving on Atari? Rainbow is all you need! This is a step-by-step tutorial from DQN to Rainbow. Every chapter contains bo
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
This repository contains small projects related to Neural Networks and Deep Learning in general.
ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p
StarGAN - Official PyTorch Implementation (CVPR 2018)
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Code for the paper "Jukebox: A Generative Model for Music"
Status: Archive (code is provided as-is, no updates expected) Jukebox Code for "Jukebox: A Generative Model for Music" Paper Blog Explorer Colab Insta
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset
AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification Code for the paper Convolutional Neural Networks for Sentence Classification (EMNLP 2014). R