7236 Repositories
Python Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset Libraries
Predicting diabetes over a five year period using logistic regression and the Pima First-Nation dataset
Diabetes This script uses the Pima First Nations dataset to create a model to predict whether or not an individual will develop Diabetes Mellitus Type
Train an imgs.ai model on your own dataset
imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings.
League of Legends Reinforcement Learning Environment (LoLRLE) multiple training scenarios using PPO.
League of Legends Reinforcement Learning Environment (LoLRLE) About This repo contains code to train an agent to play league of legends in a distribut
Code for "Optimizing risk-based breast cancer screening policies with reinforcement learning"
Tempo: Optimizing risk-based breast cancer screening policies with reinforcement learning Introduction This repository was used to develop Tempo, as d
This is a JAX implementation of Neural Radiance Fields for learning purposes.
learn-nerf This is a JAX implementation of Neural Radiance Fields for learning purposes. I've been curious about NeRF and its follow-up work for a whi
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"
NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B
DeepOBS: A Deep Learning Optimizer Benchmark Suite
DeepOBS - A Deep Learning Optimizer Benchmark Suite DeepOBS is a benchmarking suite that drastically simplifies, automates and improves the evaluation
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
LAnguage Model Analysis
LAMA: LAnguage Model Analysis LAMA is a probe for analyzing the factual and commonsense knowledge contained in pretrained language models. The dataset
A Pytorch implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU_pytorch A Pytorch Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/ab
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER. @inproceedings{tedes
Count the MACs / FLOPs of your PyTorch model.
THOP: PyTorch-OpCounter How to install pip install thop (now continously intergrated on Github actions) OR pip install --upgrade git+https://github.co
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene
Pre-trained Deep Learning models and demos (high quality and extremely fast)
OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi
This repository contains the source code of our work on designing efficient CNNs for computer vision
Efficient networks for Computer Vision This repo contains source code of our work on designing efficient networks for different computer vision tasks:
PlaidML is a framework for making deep learning work everywhere.
A platform for making deep learning work everywhere. Documentation | Installation Instructions | Building PlaidML | Contributing | Troubleshooting | R
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P
AdamW optimizer and cosine learning rate annealing with restarts
AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine
Pytorch implementation of Learning Rate Dropout.
Learning-Rate-Dropout Pytorch implementation of Learning Rate Dropout. Paper Link: https://arxiv.org/pdf/1912.00144.pdf Train ResNet-34 for Cifar10: r
PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM)
Neuro-Symbolic Sudoku Solver PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM). Please n
Robot Reinforcement Learning on the Constraint Manifold
Implementation of "Robot Reinforcement Learning on the Constraint Manifold"
PyTorch common framework to accelerate network implementation, training and validation
pytorch-framework PyTorch common framework to accelerate network implementation, training and validation. This framework is inspired by works from MML
Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"
CCOP Code of our paper Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning Requirement Install OpenSelfSup Install Detectron2
Learning objective: Use React.js, Axios, and CSS to build a responsive YouTube clone app
Learning objective: Use React.js, Axios, and CSS to build a responsive YouTube clone app to search for YouTube videos, channels, playlists, and live events via wrapper around Google YouTube API.
Official PyTorch implemention of our paper "Learning to Rectify for Robust Learning with Noisy Labels".
WarPI The official PyTorch implemention of our paper "Learning to Rectify for Robust Learning with Noisy Labels". Run python main.py --corruption_type
Selenium Page Object Model with Python
Page-object-model (POM) is a pattern that you can apply it to develop efficient automation framework.
Source code for Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning
Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning Official implementation of ACC, described in the paper "Adaptively Calibrated C
DuBE: Duple-balanced Ensemble Learning from Skewed Data
DuBE: Duple-balanced Ensemble Learning from Skewed Data "Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning" (IEEE ICDE 2022 S
Fast mesh denoising with data driven normal filtering using deep variational autoencoders
Fast mesh denoising with data driven normal filtering using deep variational autoencoders This is an implementation for the paper entitled "Fast mesh
IMBENS: class-imbalanced ensemble learning in Python.
IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a
Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust.
Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning
SPCL SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning Update on 2021/11/25: ArXiv Ver
Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes'
PEBAL This repo contains the Pytorch implementation of our paper: Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urba
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".
Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer
This repository provides a basic implementation of our GCPR 2021 paper "Learning Conditional Invariance through Cycle Consistency"
Learning Conditional Invariance through Cycle Consistency This repository provides a basic TensorFlow 1 implementation of the proposed model in our GC
Deep Learning Emotion decoding using EEG data from Autism individuals
Deep Learning Emotion decoding using EEG data from Autism individuals This repository includes the python and matlab codes using for processing EEG 2D
An Unbiased Learning To Rank Algorithms (ULTRA) toolbox
Unbiased Learning to Rank Algorithms (ULTRA) This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiment
KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution
KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc
Implementation of Change-Based Exploration Transfer (C-BET)
Implementation of Change-Based Exploration Transfer (C-BET), as presented in Interesting Object, Curious Agent: Learning Task-Agnostic Exploration.
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks Official implementation of paper Towards Practic
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data Authors: Yi-Chang Chen, Yu-Chuan Chang, Yen-Cheng Chang and Yi-Ren Ye
GMFlow: Learning Optical Flow via Global Matching
GMFlow GMFlow: Learning Optical Flow via Global Matching Authors: Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, Dacheng Tao We streamline the
Testability-Aware Low Power Controller Design with Evolutionary Learning, ITC2021
Testability-Aware Low Power Controller Design with Evolutionary Learning This repo contains the source code of Testability-Aware Low Power Controller
An open-source Kazakh named entity recognition dataset (KazNERD), annotation guidelines, and baseline NER models.
Kazakh Named Entity Recognition This repository contains an open-source Kazakh named entity recognition dataset (KazNERD), named entity annotation gui
Simple command line tool to train and deploy your machine learning models with AWS SageMaker
metamaker Simple command line tool to train and deploy your machine learning models with AWS SageMaker Features metamaker enables you to: Build a dock
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.
FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe
[CIKM 2021] Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning
Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. This repo contains the PyTorch code and implementation for the paper E
This repo contains simple to use, pretrained/training-less models for speaker diarization.
PyDiar This repo contains simple to use, pretrained/training-less models for speaker diarization. Supported Models Binary Key Speaker Modeling Based o
A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
Official Pytorch Code for the paper TransWeather
TransWeather Official Code for the paper TransWeather, Arxiv Tech Report 2021 Paper | Website About this repo: This repo hosts the implentation code,
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model
Codebase for Amodal Segmentation through Out-of-Task andOut-of-Distribution Generalization with a Bayesian Model
A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks
A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks without the use of any outside machine learning libraries - all from scratch.
An optimized prompt tuning strategy comparable to fine-tuning across model scales and tasks.
P-tuning v2 P-Tuning v2: Prompt Tuning Can Be Comparable to Finetuning Universally Across Scales and Tasks An optimized prompt tuning strategy achievi
Redis OM Python makes it easy to model Redis data in your Python applications.
Object mapping, and more, for Redis and Python Redis OM Python makes it easy to model Redis data in your Python applications. Redis OM Python | Redis
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option
A procedural Blender pipeline for photorealistic training image generation
BlenderProc2 A procedural Blender pipeline for photorealistic rendering. Documentation | Tutorials | Examples | ArXiv paper | Workshop paper Features
Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning.
Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive
Fake videos detection by tracing the source using video hashing retrieval.
Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake Videos 🎉️ 📜 Directory Introduction VTL Trace Samples and Acc of Hash
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN
Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera.
Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera. This project prepares training and testing data for various deep learning projects such as 6D object pose estimation projects singleshotpose, as well as object detection and instance segmentation projects.
Pytorch implementation for Patient Knowledge Distillation for BERT Model Compression
Patient Knowledge Distillation for BERT Model Compression Knowledge distillation for BERT model Installation Run command below to install the environm
Pytorch Lightning code guideline for conferences
Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges
LSUN Dataset Documentation and Demo Code
LSUN Please check LSUN webpage for more information about the dataset. Data Release All the images in one category are stored in one lmdb database fil
Training open neural machine translation models
Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma
An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.
About This repository shows how Autonomous Learning Library can be used to build new reinforcement learning agents. In particular, it contains a model
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Learning from graph data using Keras
Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda
A new test set for ImageNet
ImageNetV2 The ImageNetV2 dataset contains new test data for the ImageNet benchmark. This repository provides associated code for assembling and worki
An updated version of virtual model making
Model-Swap-Face v2 这个项目是基于stylegan2 pSp制作的,比v1版本Model-Swap-Face在推理速度和图像质量上有一定提升。主要的功能是将虚拟模特进行环球不同区域的风格转换,目前转换器提供西欧模特、东亚模特和北非模特三种主流的风格样式,可帮我们实现生产资料零成
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Keras Model Implementation Walkthrough
Keras Model Implementation Walkthrough
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite.
TFLite-MobileStereoNet Python scripts for performing stereo depth estimation using the MobileStereoNet model in Tensorflow Lite. Stereo depth estimati
TLoL (Python Module) - League of Legends Deep Learning AI (Research and Development)
TLoL-py - League of Legends Deep Learning Library TLoL-py is the Python component of the TLoL League of Legends deep learning library. It provides a s
A logistic regression model for health insurance purchasing prediction
Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur
An index of algorithms for learning causality with data
awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{
Haystack is an open source NLP framework that leverages Transformer models.
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model
Simple and Distributed Machine Learning
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei
Qlib is an AI-oriented quantitative investment platform
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment.
Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.
Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions
High performance distributed framework for training deep learning recommendation models based on PyTorch.
PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It
大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、DeepWalk、SSR、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、ListWise等
(中文文档|简体中文|English) 什么是推荐系统? 推荐系统是在互联网信息爆炸式增长的时代背景下,帮助用户高效获得感兴趣信息的关键; 推荐系统也是帮助产品最大限度吸引用户、留存用户、增加用户粘性、提高用户转化率的银弹。 有无数优秀的产品依靠用户可感知的推荐系统建立了良好的口碑,也有无数的公司依
Conversational text Analysis using various NLP techniques
PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"
🆕 Are you looking for a new YOLOv3 implemented by TF2.0 ? If you hate the fucking tensorflow1.x very much, no worries! I have implemented a new YOLOv
Use tensorflow to implement a Deep Neural Network for real time lane detection
LaneNet-Lane-Detection Use tensorflow to implement a Deep Neural Network for real time lane detection mainly based on the IEEE IV conference paper "To
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
Monk - A computer vision toolkit for everyone Why use Monk Issue: Want to begin learning computer vision Solution: Start with Monk's hands-on study ro
alfred-py: A deep learning utility library for **human**
Alfred Alfred is command line tool for deep-learning usage. if you want split an video into image frames or combine frames into a single video, then a
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
SinGAN Project | Arxiv | CVF | Supplementary materials | Talk (ICCV`19) Official pytorch implementation of the paper: "SinGAN: Learning a Generative M
We are building an open database of COVID-19 cases with chest X-ray or CT images.
🛑 Note: please do not claim diagnostic performance of a model without a clinical study! This is not a kaggle competition dataset. Please read this pa
SMPL-X: A new joint 3D model of the human body, face and hands together
SMPL-X: A new joint 3D model of the human body, face and hands together [Paper Page] [Paper] [Supp. Mat.] Table of Contents License Description News I
Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"
OANet implementation Pytorch implementation of OANet for ICCV'19 paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network", by
Code release for Local Light Field Fusion at SIGGRAPH 2019
Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion
Automatically download the cwru data set, and then divide it into training data set and test data set
Automatically download the cwru data set, and then divide it into training data set and test data set.自动下载cwru数据集,然后分训练数据集和测试数据集
Python scripts for performing stereo depth estimation using the MobileStereoNet model in ONNX
ONNX-MobileStereoNet Python scripts for performing stereo depth estimation using the MobileStereoNet model in ONNX Stereo depth estimation on the cone
Forecasting prices using Facebook/Meta's Prophet model
CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Generate text captions for images from their CLIP embeddings. Includes PyTorch model code and example training script.
clip-text-decoder Generate text captions for images from their CLIP embeddings. Includes PyTorch model code and example training script. Example Predi