5601 Repositories
Python learning-to-search Libraries
PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)
PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)
Framework to build and train RL algorithms
RayLink RayLink is a RL framework used to build and train RL algorithms. RayLink was used to build a RL framework, and tested in a large-scale multi-a
Uses WiFi signals :signal_strength: and machine learning to predict where you are
Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.
[ICCV '21] In this repository you find the code to our paper Keypoint Communities
Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
Vision-and-Language Navigation in Continuous Environments using Habitat
Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations
Tribuo - A Java machine learning library
Tribuo - A Java prediction library (v4.1) Tribuo is a machine learning library in Java that provides multi-class classification, regression, clusterin
Awesome Weak-Shot Learning
Awesome Weak-Shot Learning In weak-shot learning, all categories are split into non-overlapped base categories and novel categories, in which base cat
A game theoretic approach to explain the output of any machine learning model.
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis
StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110
NVIDIA Deep Learning Examples for Tensor Cores
NVIDIA Deep Learning Examples for Tensor Cores Introduction This repository provides State-of-the-Art Deep Learning examples that are easy to train an
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
Crawl the information of a given keyword on Google search engine
Crawl the information of a given keyword on Google search engine
This project aims to segment 4 common retinal lesions from Fundus Images.
This project aims to segment 4 common retinal lesions from Fundus Images.
Official Pytorch implementation of Meta Internal Learning
Official Pytorch implementation of Meta Internal Learning
Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
Learning High-Speed Flight in the Wild
Learning High-Speed Flight in the Wild This repo contains the code associated to the paper Learning Agile Flight in the Wild. For more information, pl
Machine Learning Algorithms
Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with
Learning to Reach Goals via Iterated Supervised Learning
Vanilla GCSL This repository contains a vanilla implementation of "Learning to Reach Goals via Iterated Supervised Learning" proposed by Dibya Gosh et
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.
Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression
Neural network for recognizing the gender of people in photos
Neural Network For Gender Recognition How to test it? Install requirements.txt file using pip install -r requirements.txt command Run nn.py using pyth
Algorithmic and AI MIDI Drums Generator Implementation
Algorithmic and AI MIDI Drums Generator Implementation
Modified Version Of Media Search bot
Modified Version Of Media Search bot
Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)
Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)
A geometric deep learning pipeline for predicting protein interface contacts.
A geometric deep learning pipeline for predicting protein interface contacts.
🎓Automatically Update CV Papers Daily using Github Actions (Update at 12:00 UTC Every Day)
🎓Automatically Update CV Papers Daily using Github Actions (Update at 12:00 UTC Every Day)
Deep learning algorithms for muon momentum estimation in the CMS Trigger System
Deep learning algorithms for muon momentum estimation in the CMS Trigger System The Compact Muon Solenoid (CMS) is a general-purpose detector at the L
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"
StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110
A Robust Avatar Generator with a huge number of templates
CoolAvatars Welcome to this repository of CoolAvatars. Using this project, you can generate cool avatars not only from the samples present in my image
using Machine Learning Algorithm to classification AppleStore application
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
The Hitchiker's Guide to PyTorch
The Hitchiker's Guide to PyTorch
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference Scheduling, Job Shop Scheduling, Bin Packing and many more planning problems.
Graphsignal is a machine learning model monitoring platform.
Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model performance and availability.
This is a public repo where code samples are stored for the book Practical MLOps.
[Book-2021] Practical MLOps O'Reilly Book
XManager: A framework for managing machine learning experiments 🧑🔬
XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction with experiments is done via XManager's APIs through Python launch scripts.
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
Embodied Intelligence via Learning and Evolution
Embodied Intelligence via Learning and Evolution This is the code for the paper Embodied Intelligence via Learning and Evolution Agrim Gupta, Silvio S
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021)
Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces(ICML 2021) This repository contains the code
DeepCAD: A Deep Generative Network for Computer-Aided Design Models
DeepCAD This repository provides source code for our paper: DeepCAD: A Deep Generative Network for Computer-Aided Design Models Rundi Wu, Chang Xiao,
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation
Code generation and code search for Python and Javascript.
Codeon Code generation and code search for Python and Javascript. Similar to GitHub Copilot with one major difference: Code search is leveraged to mak
PyTorch implementation of Weak-shot Fine-grained Classification via Similarity Transfer
SimTrans-Weak-Shot-Classification This repository contains the official PyTorch implementation of the following paper: Weak-shot Fine-grained Classifi
Eland is a Python Elasticsearch client for exploring and analyzing data in Elasticsearch with a familiar Pandas-compatible API.
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
A Python library for choreographing your machine learning research.
A Python library for choreographing your machine learning research.
Dynamic Realtime Animation Control
Our project is targeted at making an application that dynamically detects the user’s expressions and gestures and projects it onto an animation software which then renders a 2D/3D animation realtime that gets broadcasted live.
DGCNN - Dynamic Graph CNN for Learning on Point Clouds
DGCNN is the author's re-implementation of Dynamic Graph CNN, which achieves state-of-the-art performance on point-cloud-related high-level tasks including category classification, semantic segmentation and part segmentation.
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.
customer churn prediction prevention in telecom industry using machine learning and survival analysis
Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l
Code for 'Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning', ICCV 2021
CMIC-Retrieval Code for Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning. ICCV 2021. Introduction In this wo
AirLoop: Lifelong Loop Closure Detection
AirLoop This repo contains the source code for paper: Dasong Gao, Chen Wang, Sebastian Scherer. "AirLoop: Lifelong Loop Closure Detection." arXiv prep
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️
Make your master artistic punk avatar through machine learning world famous paintings
Master-art-punk Make your master artistic punk avatar through machine learning world famous paintings. 通过机器学习世界名画制作属于你的大师级艺术朋克头像 Nowadays, NFT is beco
2021 Machine Learning Security Evasion Competition
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang
A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery
PiSL A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery. Sun, F., Liu, Y. and Sun, H., 2021. Physics-informe
googler is a power tool to Google (web, news, videos and site search) from the command-line.
googler is a power tool to Google (web, news, videos and site search) from the command-line.
This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"
Differentiable Volumetric Rendering Paper | Supplementary | Spotlight Video | Blog Entry | Presentation | Interactive Slides | Project Page This repos
PyTorch implementation of paper "IBRNet: Learning Multi-View Image-Based Rendering", CVPR 2021.
IBRNet: Learning Multi-View Image-Based Rendering PyTorch implementation of paper "IBRNet: Learning Multi-View Image-Based Rendering", CVPR 2021. IBRN
GRF: Learning a General Radiance Field for 3D Representation and Rendering
GRF: Learning a General Radiance Field for 3D Representation and Rendering [Paper] [Video] GRF: Learning a General Radiance Field for 3D Representatio
We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning Update: The lastest code will be updated in this branch. Pleas
The first public PyTorch implementation of Attentive Recurrent Comparators
arc-pytorch PyTorch implementation of Attentive Recurrent Comparators by Shyam et al. A blog explaining Attentive Recurrent Comparators Visualizing At
Training RNNs as Fast as CNNs
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
A PyTorch Library for Accelerating 3D Deep Learning Research
Kaolin: A Pytorch Library for Accelerating 3D Deep Learning Research Overview NVIDIA Kaolin library provides a PyTorch API for working with a variety
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp
Bald-to-Hairy Translation Using CycleGAN
GANiry: Bald-to-Hairy Translation Using CycleGAN Official PyTorch implementation of GANiry. GANiry: Bald-to-Hairy Translation Using CycleGAN, Fidan Sa
[IROS'21] SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning
SurRoL IROS 2021 SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning Features dVRK compati
[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax
[NeurIPS 2021] Galerkin Transformer: linear attention without softmax Summary A non-numerical analyst oriented explanation on Toward Data Science abou
Wagtail CLIP allows you to search your Wagtail images using natural language queries.
Wagtail CLIP allows you to search your Wagtail images using natural language queries.
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. This library provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other libraries.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Educational python for Neural Networks, written in pure Python/NumPy.
Educational python for Neural Networks, written in pure Python/NumPy.
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd
Real-Time Social Distance Monitoring tool using Computer Vision
Social Distance Detector A Real-Time Social Distance Monitoring Tool Table of Contents Motivation YOLO Theory Detection Output Tech Stack Functionalit
Transfer-Learn is an open-source and well-documented library for Transfer Learning.
Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021) Jiaxi Jiang, Kai Zhang, Radu Timofte Computer Vision Lab, ETH Zurich, Switzerland 🔥
Rhythm-Finder is a unsupervised ML driven python powered web-application that can find the songs that suits you.
ML-powered Music Recommendation Engine
Awesome Long-Tailed Learning
Awesome Long-Tailed Learning This repo pays specially attention to the long-tailed distribution, where labels follow a long-tailed or power-law distri
CLIPort: What and Where Pathways for Robotic Manipulation
CLIPort CLIPort: What and Where Pathways for Robotic Manipulation Mohit Shridhar, Lucas Manuelli, Dieter Fox CoRL 2021 CLIPort is an end-to-end imitat
Exploring Relational Context for Multi-Task Dense Prediction [ICCV 2021]
Adaptive Task-Relational Context (ATRC) This repository provides source code for the ICCV 2021 paper Exploring Relational Context for Multi-Task Dense
Official Implementation of 'UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers' ICLR 2021(spotlight)
UPDeT Official Implementation of UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers (ICLR 2021 spotlight) The
Free Book about Deep-Learning approaches for Chess (like AlphaZero, Leela Chess Zero and Stockfish NNUE)
Free Book about Deep-Learning approaches for Chess (like AlphaZero, Leela Chess Zero and Stockfish NNUE)
A Python library for Deep Probabilistic Modeling
Abstract DeeProb-kit is a Python library that implements deep probabilistic models such as various kinds of Sum-Product Networks, Normalizing Flows an
A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You can find two approaches for achieving this in this repo.
multitask-learning-transformers A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You
[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
EPCDepth EPCDepth is a self-supervised monocular depth estimation model, whose supervision is coming from the other image in a stereo pair. Details ar
Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images (ICCV 2021)
Table of Content Introduction Getting Started Datasets Installation Experiments Training & Testing Pretrained models Texture fine-tuning Demo Toward R
A curated (most recent) list of resources for Learning with Noisy Labels
A curated (most recent) list of resources for Learning with Noisy Labels
Reinforcement learning framework and algorithms implemented in PyTorch.
Reinforcement learning framework and algorithms implemented in PyTorch.
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their
Research Artifact of USENIX Security 2022 Paper: Automated Side Channel Analysis of Media Software with Manifold Learning
Manifold-SCA Research Artifact of USENIX Security 2022 Paper: Automated Side Channel Analysis of Media Software with Manifold Learning The repo is org
The Ultimate FREE Machine Learning Study Plan
The Ultimate FREE Machine Learning Study Plan
A comprehensive repository containing 30+ notebooks on learning machine learning!
A comprehensive repository containing 30+ notebooks on learning machine learning!
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models tabular data.