7236 Repositories
Python Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset Libraries
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021.
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f
KUIZ is a web application quiz where you can create/take a quiz for learning and sharing knowledge from various subjects, questions and answers.
KUIZ KUIZ is a web application quiz where you can create/take a quiz for learning and sharing knowledge from various subjects, questions and answers.
Repository for the Bias Benchmark for QA dataset.
BBQ Repository for the Bias Benchmark for QA dataset. Authors: Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Tho
Painting app using Python machine learning and vision technology.
AI Painting App We are making an app that will track our hand and helps us to draw from that. We will be using the advance knowledge of Machine Learni
Open source style Deep Dream project
DeepDream ⚠️ If you don't have a gpu with cuda, the style transfer execution time will be much longer Prerequisites Python =3.8.10 How to Install sud
ProMP: Proximal Meta-Policy Search
ProMP: Proximal Meta-Policy Search Implementations corresponding to ProMP (Rothfuss et al., 2018). Overall this repository consists of two branches: m
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
Minimalistic Gridworld Environment (MiniGrid)
Minimalistic Gridworld Environment (MiniGrid) There are other gridworld Gym environments out there, but this one is designed to be particularly simple
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai
Hapi is a Python library for building Conceptual Distributed Model using HBV96 lumped model & Muskingum routing method
Current build status All platforms: Current release info Name Downloads Version Platforms Hapi - Hydrological library for Python Hapi is an open-sourc
Medical image analysis framework merging ANTsPy and deep learning
ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas
SCAAML is a deep learning framwork dedicated to side-channel attacks run on top of TensorFlow 2.x.
SCAAML (Side Channel Attacks Assisted with Machine Learning) is a deep learning framwork dedicated to side-channel attacks. It is written in python and run on top of TensorFlow 2.x.
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021
Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021
object recognition with machine learning on Respberry pi
Respberrypi_object-recognition object recognition with machine learning on Respberry pi line.py 建立一支與樹梅派連線的 linebot 使用此 linebot 遠端控制樹梅派拍照 config.ini l
Multiview 3D object detection on MultiviewC dataset through moft3d.
Multiview Orthographic Feature Transformation for 3D Object Detection Multiview 3D object detection on MultiviewC dataset through moft3d. Introduction
CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning applications.
SmartSim Example Zoo This repository contains CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning appl
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch.
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!!
GUI for a Vocal Remover that uses Deep Neural Networks.
GUI for a Vocal Remover that uses Deep Neural Networks.
A style-based Quantum Generative Adversarial Network
Style-qGAN A style based Quantum Generative Adversarial Network (style-qGAN) model for Monte Carlo event generation. Tutorial We have prepared a noteb
SoGCN: Second-Order Graph Convolutional Networks
SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py
Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".
DeepOrder Implementation of DeepOrder for the paper "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing". Project
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations
Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr
Official code for Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset
Official code for our Interspeech 2021 - Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset [1]*. Visually-grounded spoken language datasets c
This is a library for training and applying sparse fine-tunings with torch and transformers.
This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f
Human4D Dataset tools for processing and visualization
HUMAN4D: A Human-Centric Multimodal Dataset for Motions & Immersive Media HUMAN4D constitutes a large and multimodal 4D dataset that contains a variet
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.
Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima
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
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Pytorch implementation of the paper: "A Unified Framework for Separating Superimposed Images", in CVPR 2020.
Deep Adversarial Decomposition PDF | Supp | 1min-DemoVideo Pytorch implementation of the paper: "Deep Adversarial Decomposition: A Unified Framework f
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
ESRGAN (Enhanced SRGAN) [ 🚀 BasicSR] [Real-ESRGAN] ✨ New Updates. We have extended ESRGAN to Real-ESRGAN, which is a more practical algorithm for rea
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”
A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte
Code for reproducing experiments in "Improved Training of Wasserstein GANs"
Improved Training of Wasserstein GANs Code for reproducing experiments in "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, Tensor
Deep Residual Networks with 1K Layers
Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc
Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers.
ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset
A torch.Tensor-like DataFrame library supporting multiple execution runtimes and Arrow as a common memory format
TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou
Collection of Docker images for ML/DL and video processing projects
Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real Time Video Interpolation arXiv | YouTube | Colab | Tutorial | Demo Table of Contents Introduction Collection Usage Evaluation Training and
Youtube Downloader is a Graphic User Interface(GUI) that lets users download a Youtube Video or Audio through a URL
Youtube Downloader This Python and Tkinter based GUI allows users to directly download the Best Resolution Videos and Audios from Youtube. Pa-fy Insta
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch
revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f
Bittensor - an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence
At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.
Solutions of Reinforcement Learning 2nd Edition
Solutions of Reinforcement Learning, An Introduction
LibreLingo🐢 🌎 📚 a community-owned language-learning platform
LibreLingo's mission is to create a modern language-learning platform that is owned by the community of its users. All software is licensed under AGPLv3, which guarantees the freedom to run, study, share, and modify the software. Course authors are encouraged to release their courses with free licenses.
A JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short.
BraVe This is a JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short. The model provided in this package wa
BLEURT is a metric for Natural Language Generation based on transfer learning.
BLEURT: a Transfer Learning-Based Metric for Natural Language Generation BLEURT is an evaluation metric for Natural Language Generation. It takes a pa
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a
A GOOD REPRESENTATION DETECTS NOISY LABELS
A GOOD REPRESENTATION DETECTS NOISY LABELS This code is a PyTorch implementation of the paper: Prerequisites Python 3.6.9 PyTorch 1.7.1 Torchvision 0.
Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.
DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Preprocess file of the dataset used in implicit sub-populations: (Demographic groups
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"
DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit
Release of the ConditionalQA dataset
ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning
DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts
Deep Sea Treasure Environment for Multi-Objective Optimization Research
DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip
Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification
next_best_view_rl Setup Clone the repository: git clone --recurse-submodules ... In 'third_party/zed-ros-wrapper': git checkout devel Install mujoco `
A cross-lingual COVID-19 fake news dataset
CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,
Codebase of deep learning models for inferring stability of mRNA molecules
Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen
This is an official pytorch implementation of Fast Fourier Convolution.
Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma
Direct design of biquad filter cascades with deep learning by sampling random polynomials.
IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Explaining in Style: Official TensorFlow Colab Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman,
The source code for 'Noisy-Labeled NER with Confidence Estimation' accepted by NAACL 2021
Kun Liu*, Yao Fu*, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, Sheng Gao. Noisy-Labeled NER with Confidence Estimation. NAACL 2021. [arxiv]
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"
DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection, AAAI 2021.
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection This repository is an official implementation of the AAAI 2021 paper Co-mi
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.
mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do
A PyTorch implementation of paper "Learning Shared Semantic Space for Speech-to-Text Translation", ACL (Findings) 2021
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant
African language Speech Recognition - Speech-to-Text
Swahili-Speech-To-Text Table of Contents Swahili-Speech-To-Text Overview Scenario Approach Project Structure data: models: notebooks: scripts tests: l
A collection of learning outcomes data analysis using Python and SQL, from DQLab.
Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu
Python Package for DataHerb: create, search, and load datasets.
The Python Package for DataHerb A DataHerb Core Service to Create and Load Datasets.
An end-to-end regression problem of predicting the price of properties in Bangalore.
Bangalore-House-Price-Prediction An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.
The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.
The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.
RL-driven agent playing tic-tac-toe on starknet against challengers.
tictactoe-on-starknet RL-driven agent playing tic-tac-toe on starknet against challengers. GUI reference: https://pythonguides.com/create-a-game-using
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.
The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering
[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt
A synthetic texture-invariant dataset for object detection of UAVs
A synthetic dataset for object detection of UAVs This repository contains a synthetic datasets accompanying the paper Sim2Air - Synthetic aerial datas