6302 Repositories
Python deep-learning-models Libraries
The code of "Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer".
Code data_preprocess.py: preprocess data for Dependent-T5. parameters.py: define parameters of Dependent-T5. train_tools.py: traning and evaluation co
Code of the paper "Shaping Visual Representations with Attributes for Few-Shot Learning (ASL)".
Shaping Visual Representations with Attributes for Few-Shot Learning This code implements the Shaping Visual Representations with Attributes for Few-S
Active learning for Mask R-CNN in Detectron2
MaskAL - Active learning for Mask R-CNN in Detectron2 Summary MaskAL is an active learning framework that automatically selects the most-informative i
Integrate GraphQL with your Pydantic models
graphene-pydantic A Pydantic integration for Graphene. Installation pip install "graphene-pydantic" Examples Here is a simple Pydantic model: import u
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding
Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ↔ transc
Using image super resolution models with vapoursynth and speeding them up with TensorRT
vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since
Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Unsupervised JPEG Domain Adaptation for Practical Digital Image Forensics @WIFS2021 (Montpellier, France) Rony Abecidan, Vincent Itier, Jeremie Boulan
[TNNLS 2021] The official code for the paper "Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement"
CSDNet-CSDGAN this is the code for the paper "Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement" Environment Preparing pyt
A PyTorch implementation of deep-learning-based registration
DiffuseMorph Implementation A PyTorch implementation of deep-learning-based registration. Requirements OS : Ubuntu / Windows Python 3.6 PyTorch 1.4.0
Code for paper: "Spinning Language Models for Propaganda-As-A-Service"
Spinning Language Models for Propaganda-As-A-Service This is the source code for the Arxiv version of the paper. You can use this Google Colab to expl
Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"
Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem
Code basis for the paper "Camera Condition Monitoring and Readjustment by means of Noise and Blur" (2021)
Camera Condition Monitoring and Readjustment by means of Noise and Blur This repository contains the source code of the paper: Wischow, M., Gallego, G
Code for 'Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning' (AAAI 2022)
Blockwise Sequential Model Learning Code for 'Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning' (AAAI 2022) For ins
A FAIR dataset of TCV experimental results for validating edge/divertor turbulence models.
TCV-X21 validation for divertor turbulence simulations Quick links Intro Welcome to TCV-X21. We're glad you've found us! This repository is designed t
Pydantic models for pywttr and aiopywttr.
Pydantic models for pywttr and aiopywttr.
A minimal, standalone viewer for 3D animations stored as stop-motion sequences of individual .obj mesh files.
ObjSequenceViewer V0.5 A minimal, standalone viewer for 3D animations stored as stop-motion sequences of individual .obj mesh files. Installation: pip
PyTorch implementation of normalizing flow models
PyTorch implementation of normalizing flow models
Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts
t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that
How the Deep Q-learning method works and discuss the new ideas that makes the algorithm work
Deep Q-Learning Recommend papers The first step is to read and understand the method that you will implement. It was first introduced in a 2013 paper
A PyTorch library and evaluation platform for end-to-end compression research
CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c
Jiminy, fast and portable Python/C++ simulator of poly-articulated systems with OpenAI Gym interface for reinforcement learning.
Jiminy is a fast and portable cross-platform open-source simulator for poly-articulated systems. It was built with two ideas in mind: provide a fast y
PyAbsorp is a python module that has the main focus to help estimate the Sound Absorption Coefficient.
This is a package developed to be use to find the Sound Absorption Coefficient through some implemented models, like Biot-Allard, Johnson-Champoux and
SeqAttack: a framework for adversarial attacks on token classification models
A framework for adversarial attacks against token classification models
Computer Vision Script to recognize first person motion, developed as final project for the course "Machine Learning and Deep Learning"
Overview of The Code BaseColab/MLDL_FPAR.pdf: it contains the full explanation of our work Base Colab: it contains the base colab used to perform all
1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task
KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a
Users can free try their models on SIDD dataset based on this code
SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p
PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle
The code for "Deep Level Set for Box-supervised Instance Segmentation in Aerial Images".
Deep Levelset for Box-supervised Instance Segmentation in Aerial Images Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu* Any questions or discussions ar
A `Neural = Symbolic` framework for sound and complete weighted real-value logic
Logical Neural Networks LNNs are a novel Neuro = symbolic framework designed to seamlessly provide key properties of both neural nets (learning) and s
Official implementation of the AAAI 2022 paper "Learning Token-based Representation for Image Retrieval"
Token: Token-based Representation for Image Retrieval PyTorch training code for Token-based Representation for Image Retrieval. We propose a joint loc
easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.
easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required.
A system for quickly generating training data with weak supervision
Programmatically Build and Manage Training Data Announcement The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI applicat
Synthetic Data Generation for tabular, relational and time series data.
An Open Source Project from the Data to AI Lab, at MIT Website: https://sdv.dev Documentation: https://sdv.dev/SDV User Guides Developer Guides Github
Flexible HDF5 saving/loading and other data science tools from the University of Chicago
deepdish Flexible HDF5 saving/loading and other data science tools from the University of Chicago. This repository also host a Deep Learning blog: htt
Deep Difference and search of any Python object/data.
DeepDiff v 5.6.0 DeepDiff Overview DeepDiff: Deep Difference of dictionaries, iterables, strings and other objects. It will recursively look for all t
Official code of IterMVS
IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear
An efficient toolkit for Face Stylization based on the paper "AgileGAN: Stylizing Portraits by Inversion-Consistent Transfer Learning"
MMGEN-FaceStylor English | 简体中文 Introduction This repo is an efficient toolkit for Face Stylization based on the paper "AgileGAN: Stylizing Portraits
Code for ShadeGAN (NeurIPS2021) A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Project Page | Paper A Shading-Guided Generative Implicit Model
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o
Codes for CyGen, the novel generative modeling framework proposed in "On the Generative Utility of Cyclic Conditionals" (NeurIPS-21)
On the Generative Utility of Cyclic Conditionals This repository is the official implementation of "On the Generative Utility of Cyclic Conditionals"
Autoregressive Models in PyTorch.
Autoregressive This repository contains all the necessary PyTorch code, tailored to my presentation, to train and generate data from WaveNet-like auto
Models, datasets and tools for Facial keypoints detection
Template for Data Science Project This repo aims to give a robust starting point to any Data Science related project. It contains readymade tools setu
Learning a Little about Containerlab
Learning a Little about Containerlab Hello all. This is the respository based on this blog post. Getting Started Feel free to use this example. You wi
Create 3d loss surface visualizations, with optimizer path. Issues welcome!
MLVTK A loss surface visualization tool Simple feed-forward network trained on chess data, using elu activation and Adam optimizer Simple feed-forward
Final term project for Bayesian Machine Learning Lecture (XAI-623)
Mixquality_AL Final Term Project For Bayesian Machine Learning Lecture (XAI-623) Youtube Link The presentation is given in YoutubeLink Problem Formula
a practicable framework used in Deep Learning. So far UDL only provide DCFNet implementation for the ICCV paper (Dynamic Cross Feature Fusion for Remote Sensing Pansharpening)
UDL UDL is a practicable framework used in Deep Learning (computer vision). Benchmark codes, results and models are available in UDL, please contact @
BT-Unet: A-Self-supervised-learning-framework-for-biomedical-image-segmentation-using-Barlow-Twins
BT-Unet: A-Self-supervised-learning-framework-for-biomedical-image-segmentation-using-Barlow-Twins Deep learning has brought most profound contributio
Official Implementation for the paper DeepFace-EMD: Re-ranking Using Patch-wise Earth Mover’s Distance Improves Out-Of-Distribution Face Identification
DeepFace-EMD: Re-ranking Using Patch-wise Earth Mover’s Distance Improves Out-Of-Distribution Face Identification Official Implementation for the pape
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"
CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch
Enhancing Column Generation by a Machine-Learning-BasedPricing Heuristic for Graph Coloring
Enhancing Column Generation by a Machine-Learning-BasedPricing Heuristic for Graph Coloring (to appear at AAAI 2022) We propose a machine-learning-bas
Machine learning Bot detection technique, based on United States election dataset
Machine learning Bot detection technique, based on United States election dataset (2020). Current github repo provides implementation described in pap
Continual learning with sketched Jacobian approximations
Continual learning with sketched Jacobian approximations This repository contains the code for reproducing figures and results in the paper ``Provable
Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”
Uncertainty Estimation Methods Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods” Reference If you use this code,
Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models
Explainable_FIQA_WITH_AMVA Note This is the official repository of the paper: Explainability of the Implications of Supervised and Unsupervised Face I
Research Artifact of USENIX Security 2022 Paper: Automated Side Channel Analysis of Media Software with Manifold Learning
Automated Side Channel Analysis of Media Software with Manifold Learning Official implementation of USENIX Security 2022 paper: Automated Side Channel
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning We propose a method to learn multiple gaits of quadruped robot us
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion
Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M
Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.
VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks. VMAgent is constructed based on one month r
Official implementation of "A Shared Representation for Photorealistic Driving Simulators" in PyTorch.
A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim
In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard test set accuracy
PixMix Introduction In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard te
This is the official code for the paper "Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision"
RUAS This is the official code for the paper "Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision" A prelimin
Official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo'
IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.
Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data.
Deep Learning Dataset Maker Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data. How to use Down
Machine Learning algorithms implementation.
Machine Learning Algorithms Machine Learning algorithms implementation. What can I find here? ML Algorithms KNN K-Means-Clustering SVM (MultiClass) Pe
An ETL framework + Monitoring UI/API (experimental project for learning purposes)
Fastlane An ETL framework for building pipelines, and Flask based web API/UI for monitoring pipelines. Project structure fastlane |- fastlane: (ETL fr
Visual Adversarial Imitation Learning using Variational Models (VMAIL)
Visual Adversarial Imitation Learning using Variational Models (VMAIL) This is the official implementation of the NeurIPS 2021 paper. Project website
A collection of models, views, middlewares, and forms to help secure a Django project.
Django-Security This package offers a number of models, views, middlewares and forms to facilitate security hardening of Django applications. Full doc
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
HDMapNet: A Local Semantic Map Learning and Evaluation Framework
HDMapNet_devkit Devkit for HDMapNet. HDMapNet: A Local Semantic Map Learning and Evaluation Framework Qi Li, Yue Wang, Yilun Wang, Hang Zhao [Paper] [
Tensorflow 2 implementations of the C-SimCLR and C-BYOL self-supervised visual representation methods from "Compressive Visual Representations" (NeurIPS 2021)
Compressive Visual Representations This repository contains the source code for our paper, Compressive Visual Representations. We developed informatio
Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"
Fourier Feature Networks and Neural Volume Rendering This repository is a companion to a lecture given at the University of Cambridge Engineering Depa
Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency
Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency This is a official implementation of the CycleContrast introduced in
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain
RuleBERT: Teaching Soft Rules to Pre-Trained Language Models
RuleBERT: Teaching Soft Rules to Pre-Trained Language Models (Paper) (Slides) (Video) RuleBERT is a pre-trained language model that has been fine-tune
PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning"
Artistic Style Transfer with Internal-external Learning and Contrastive Learning This is the official PyTorch implementation of our paper: "Artistic S
Open MLOps - A Production-focused Open-Source Machine Learning Framework
Open MLOps - A Production-focused Open-Source Machine Learning Framework Open MLOps is a set of open-source tools carefully chosen to ease user experi
Code for CVPR2019 paper《Unequal Training for Deep Face Recognition with Long Tailed Noisy Data》
Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data. This is the code of CVPR 2019 paper《Unequal Training for Deep Face Recognition
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma This is the offi
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Meta-Weight-Net NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Official Pytorch implementation for noisy labels). The
Code for Learning to Segment The Tail (LST)
Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th
Codes for "Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier"
Deep-RTC [project page] This repository contains the source code accompanying our ECCV 2020 paper. Solving Long-tailed Recognition with Deep Realistic
Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification Implementation of "Learning From Multiple Experts: Se
Official Repository for our ECCV2020 paper: Imbalanced Continual Learning with Partitioning Reservoir Sampling
Imbalanced Continual Learning with Partioning Reservoir Sampling This repository contains the official PyTorch implementation and the dataset for our
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
Rethinking the Value of Labels for Improving Class-Imbalanced Learning This repository contains the implementation code for paper: Rethinking the Valu
Repo for CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
CReST in Tensorflow 2 Code for the paper: "CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning" by Chen Wei, Ki
Official PyTorch implementation of RIO
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection Figure 1: Our proposed Resampling at image-level and obect-
Supercharging Imbalanced Data Learning WithCausal Representation Transfer
ECRT: Energy-based Causal Representation Transfer Code for Supercharging Imbalanced Data Learning With Energy-basedContrastive Representation Transfer
Machine Learning automation and tracking
The Open-Source MLOps Orchestration Framework MLRun is an open-source MLOps framework that offers an integrative approach to managing your machine-lea
ZenML 🙏: MLOps framework to create reproducible ML pipelines for production machine learning.
ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. It has a simple, flexible syntax, is cloud and tool agnostic, and has interfaces/abstractions that are catered towards ML workflows.
Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others and is truly open-source.
Flyte Flyte is a workflow automation platform for complex, mission-critical data, and ML processes at scale Home Page · Quick Start · Documentation ·
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Seldon Core: Blazing Fast, Industry-Ready ML An open source platform to deploy your machine learning models on Kubernetes at massive scale. Overview S
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us
Uni-Fold: Training your own deep protein-folding models.
Uni-Fold: Training your own deep protein-folding models. This package provides and implementation of a trainable, Transformer-based deep protein foldi