Python Graph-contrastive-learning Resources

FewCLUE: 为中文NLP定制的小样本学习测评基准

Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe

One Stop Anomaly Shop (OSAS) Quick start guide Step 1: Get/build the docker image Option 1: Use precompiled image (might not reflect latest changes):

MiVOS (CVPR 2021) - Mask Propagation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] [Papers with Code] This repo impleme

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma Paper: https://arxiv.o

MiVOS (CVPR 2021) - Scribble To Mask Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] A simplistic network that turns scri

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

OptiPrompt This is the PyTorch implementation of the paper Factual Probing Is [MASK]: Learning vs. Learning to Recall. We propose OptiPrompt, a simple

DC3: A learning method for optimization with hard constraints This repository is by Priya L. Donti, David Rolnick, and J. Zico Kolter and contains the

Python books free to read online or download

cryptos Just me developing a pure Python from-scratch zero-dependency implementation of Bitcoin for educational purposes. This includes a lot of the c

Ranger21 - integrating the latest deep learning components into a single optimizer Ranger deep learning optimizer rewrite to use newest components Ran

collie_recs Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Coll

The implementation of paper CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval. CLIP4Clip is a video-text retrieval model based

CLAP Contrastive Language-Audio Pretraining In due time this repo will be full of lovely things, I hope. Feel free to check out the Issues if you're i

Introduction This is the PyTorch implementation for Adaptive Graph Representation Learning for Video Person Re-identification. Get started git clone h

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta

arXiv Dual Contrastive Learning Adversarial Generative Networks (DCLGAN) We provide our PyTorch implementation of DCLGAN, which is a simple yet powerf

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning (NeurIPS 2020) Introduction AdaShare is a novel and differentiable approach fo

Gender Bangs Body Side Pose (Yaw) Lighting Smile Face Shape Lipstick Color Painting Style Pose (Yaw) Pose (Pitch) Zoom & Rotate Flush & Eye Color Mout

BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation This is a demo implementation of BYOL for Audio (BYOL-A), a self-sup

Lighting the Darkness in the Deep Learning Era: A Survey, An Online Platform, A New Dataset This repository provides a unified online platform, LoLi-P

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.

🏅 Collection of Kaggle Solutions and Ideas 🏅

A list of papers regarding generalization in (deep) reinforcement learning

Although Evolutionary Algorithms have shown to result in interesting behavior, they focus on learning across generations whereas behavior could also be learned during ones lifetime.

A list of multi-task learning papers and projects.

This page contains a list of papers on multi-task learning for computer vision. Please create a pull request if you wish to add anything. If you are interested, consider reading our recent survey paper.

coax is built on top of JAX, but it doesn't have an explicit dependence on the jax python package. The reason is that your version of jaxlib will depend on your CUDA version.

Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.

Representation Robustness Evaluations Our implementation is based on code from MadryLab's robustness package and Devon Hjelm's Deep InfoMax. For all t

Accelerating Reinforcement Learning with Learned Skill Priors [Project Website] [Paper] Karl Pertsch1, Youngwoon Lee1, Joseph Lim1 1CLVR Lab, Universi

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

Image Inpainting with External-internal Learning and Monochromic Bottleneck This repository is for the CVPR 2021 paper: 'Image Inpainting with Externa

Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Code for paper: Does Unsupervised Architecture Representation

clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.

CVPR 2021 | Activate or Not: Learning Customized Activation. This repository contains the official Pytorch implementation of the paper Activate or Not

SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contr

Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images.

DoDNet This repo holds the pytorch implementation of DoDNet: DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datase

XDVioDet Official implementation of "Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision" ECCV2020. The proj

This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).

SpikeX is a collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction tools with almost-zero effort.

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

Skeleton Merger Skeleton Merger, an Unsupervised Aligned Keypoint Detector. The paper is available at https://arxiv.org/abs/2103.10814. A map of the r

Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

Contrastive Tension State of the art Semantic Sentence Embeddings Published Paper · Huggingface Models · Report Bug Overview This is the official code

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility functions that allow writing model-based RL algorithms with only a few lines of code.

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Knowledge Graph,Question Answering System，基于知识图谱和向量检索的医疗诊断问答系统

Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from

Learning What To Do by Simulating the Past This repository contains code that implements the Deep Reward Learning by Simulating the Past (Deep RSLP) a

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

This is the code of "Scene Text Retrieval via Joint Text Detection and Similarity Learning". For more details, please refer to our CVPR2021 paper.

Labelled data remains a scarce resource in many practical NLP scenarios. This is especially the case when working with resource-poor languages (or text domains), or when using task-specific labels without pre-existing datasets. The only available option is often to collect and annotate texts by hand, which is expensive and time-consuming.

libmaths libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat

TransFuser This repository contains the code for the CVPR 2021 paper Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. If you find our

Spatially Consistent Representation Learning (CVPR'21) Official PyTorch implementation of Spatially Consistent Representation Learning (SCRL). This re

[PYTORCH] Deep Q-learning for playing Chrome Dino

Simple but maybe too simple config management through python data classes. We use it for machine learning.

DevResources One destination for all the developer's learning resources. Find all of your learning resources under one roof and add your own. Live ✨ Y

ReSim This repository provides the PyTorch implementation of Region Similarity Representation Learning (ReSim) described in this paper: @Article{xiao2

This repository contains code of our CVPR 2021 paper - "Learning Camera Localization via Dense Scene Matching" by Shitao Tang, Chengzhou Tang, Rui Hua

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.

LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Introduction English | 简体中文 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi

BMW Semantic Segmentation GPU/CPU Inference API This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit. The train

FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP only focuses on adavanced models and dataset, while FedML supports various federated optimizers (e.g., FedAvg) and platforms (Distributed Computing, IoT/Mobile, Standalone).

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

DeepONet: Learning nonlinear operators The source code for the paper Learning nonlinear operators via DeepONet based on the universal approximation th

Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t

PLOP: Learning without Forgetting for Continual Semantic Segmentation This repository contains all of our code. It is a modified version of Cermelli e

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

GrammarTagger — A Neural Multilingual Grammar Profiler for Language Learning GrammarTagger is an open-source toolkit for grammatical profiling for lan

NoPdb: Non-interactive Python Debugger Installation: pip install nopdb Docs: https://nopdb.readthedocs.io/ NoPdb is a programmatic (non-interactive) d

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer

Welcome to MedicalTorch MedicalTorch is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets fo

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

PyTorch for Semantic Segmentation This repository contains some models for semantic segmentation and the pipeline of training and testing models, impl

Face Recognition Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D an

Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control