5197 Repositories
Python prototypical-learning Libraries
The Hitchiker's Guide to PyTorch
The Hitchiker's Guide to PyTorch
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
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
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
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.
Deep Face Recognition in PyTorch
Face Recognition in PyTorch By Alexey Gruzdev and Vladislav Sovrasov Introduction A repository for different experimental Face Recognition models such
a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch
pytorch-spynet This is a personal reimplementation of SPyNet [1] using PyTorch. Should you be making use of this work, please cite the paper according
GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]
GANimation: Anatomically-aware Facial Animation from a Single Image [Project] [Paper] Official implementation of GANimation. In this work we introduce
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
Differentiable architecture search for convolutional and recurrent networks
Differentiable Architecture Search Code accompanying the paper DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang. arX
Learning Confidence for Out-of-Distribution Detection in Neural Networks
Learning Confidence Estimates for Neural Networks This repository contains the code for the paper Learning Confidence for Out-of-Distribution Detectio
Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)
Large-Scale Long-Tailed Recognition in an Open World [Project] [Paper] [Blog] Overview Open Long-Tailed Recognition (OLTR) is the author's re-implemen
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)
Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
Machine learning template for projects based on sklearn library.
Machine learning template for projects based on sklearn library.
An inofficial PyTorch implementation of PREDATOR based on KPConv.
PREDATOR: Registration of 3D Point Clouds with Low Overlap An inofficial PyTorch implementation of PREDATOR based on KPConv. The code has been tested
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019
PoseNet of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image" Introduction This repo is official Py
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition
Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition Currently
Some example scripts on pytorch
pytorch-practice Some example scripts on pytorch CONLL 2000 Chunking task Uses BiLSTM CRF loss with char CNN embeddings. To run use: cd data/conll2000
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P
PyTorch tutorials and best practices.
Effective PyTorch Table of Contents Part I: PyTorch Fundamentals PyTorch basics Encapsulate your model with Modules Broadcasting the good and the ugly
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
DeepNLP-models-Pytorch Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning) This is not for Pytorch be
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm
PyTorch Tutorial for Deep Learning Researchers
This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less
An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
Table of Contents: Introduction to Torch's Tensor Library Computation Graphs and Automatic Differentiation Deep Learning Building Blocks: Affine maps,
Minimal tutorials for PyTorch
Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials. Tensor multiplication Linear Regression Logistic Regression Neural Network
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone OS (Compiler)\LibTorch 1.9.0 macOS (clang 10.0, 11.0, 12.0) Linux (gcc 8, 9, 10, 11) Windows (msv
A collection of various deep learning architectures, models, and tips
Deep Learning Models A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. Traditiona
Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.
Deep Learning Materials by Deep Learning Wizard Start Learning Now Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet fr
Deep Learning (with PyTorch)
Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.
D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Book website | STAT 157 Course at UC Berkeley | Latest version
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
PyTorch Examples WARNING: if you fork this repo, github actions will run daily on it. To disable this, go to /examples/settings/actions and Disable Ac
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic
Implementation of linear CorEx and temporal CorEx.
Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx
Visualization toolkit for neural networks in PyTorch! Demo --
FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.
Implementation of the Remixer Block from the Remixer paper, in Pytorch
Remixer - Pytorch Implementation of the Remixer Block from the Remixer paper, in Pytorch. It claims that substituting the feedforwards in transformers
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
A simple but complete full-attention transformer with a set of promising experimental features from various papers
x-transformers A concise but fully-featured transformer, complete with a set of promising experimental features from various papers. Install $ pip ins
[MICCAI'20] AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes
AlignShift NEW: Code for our new MICCAI'21 paper "Asymmetric 3D Context Fusion for Universal Lesion Detection" will also be pushed to this repository
Merlion: A Machine Learning Framework for Time Series Intelligence
Merlion: A Machine Learning Library for Time Series Table of Contents Introduction Installation Documentation Getting Started Anomaly Detection Foreca
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
Python implementation of a live deep learning based age/gender/expression recognizer
TUT live age estimator Python implementation of a live deep learning based age/gender/smile/celebrity twin recognizer. All components use convolutiona