5295 Repositories
Python learning-with-confident-examples Libraries
Adversarial Examples for Extreme Multilabel Text Classification
Adversarial Examples for Extreme Multilabel Text Classification The code is adapted from the source codes of BERT-ATTACK [1], APLC_XLNet [2], and Atte
Sleep staging from ECG, assisted with EEG
Sleep_Staging_Knowledge Distillation This codebase implements knowledge distillation approach for ECG based sleep staging assisted by EEG based sleep
Type4Py: Deep Similarity Learning-Based Type Inference for Python
Type4Py: Deep Similarity Learning-Based Type Inference for Python This repository contains the implementation of Type4Py and instructions for re-produ
A GitHub action that suggests type annotations for Python using machine learning.
Typilus: Suggest Python Type Annotations A GitHub action that suggests type annotations for Python using machine learning. This action makes suggestio
AI4Good project for detecting waste in the environment
Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in
A powerful framework for decentralized federated learning with user-defined communication topology
Scatterbrained Decentralized Federated Learning Scatterbrained makes it easy to build federated learning systems. In addition to traditional federated
Coursera learning course Python the basics. Programming exercises and tasks
HSE_Python_the_basics Welcome to BAsics programming Python! Youāre joining thousands of learners currently enrolled in the course. I'm excited to have
Learning Lightweight Low-Light Enhancement Network using Pseudo Well-Exposed Images
Learning Lightweight Low-Light Enhancement Network using Pseudo Well-Exposed Images This repository contains the implementation of the following paper
This is a graphql api build using ariadne python that serves a graphql-endpoint at port 3002 to perform language translation and identification using deep learning in python pytorch.
Language Translation and Identification this machine/deep learning api that will be served as a graphql-api using ariadne, to perform the following ta
Implementation of parameterized soft-exponential activation function.
Soft-Exponential-Activation-Function: Implementation of parameterized soft-exponential activation function. In this implementation, the parameters are
Self-Supervised Learning
Self-Supervised Learning Features self_supervised offers features like modular framework support for multi-gpu training using PyTorch Lightning easy t
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
A python interface for training Reinforcement Learning bots to battle on pokemon showdown
The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru
A lightweight, pure-Python mobile robot simulator designed for experiments in Artificial Intelligence (AI) and Machine Learning, especially for Jupyter Notebooks
aitk.robots A lightweight Python robot simulator for JupyterLab, Notebooks, and other Python environments. Goals A lightweight mobile robotics simulat
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn
Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
Official implementation of the paper "Backdoor Attacks on Self-Supervised Learning".
SSL-Backdoor Abstract Large-scale unlabeled data has allowed recent progress in self-supervised learning methods that learn rich visual representation
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
Learning with Subset Stacking
Learning with Subset Stacking (LESS) LESS is a new supervised learning algorithm that is based on training many local estimators on subsets of a given
Implementation of "Semi-supervised Domain Adaptive Structure Learning"
Semi-supervised Domain Adaptive Structure Learning - ASDA This repo contains the source code and dataset for our ASDA paper. Illustration of the propo
These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations"
Few-shot-NLEs These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations". You can find the smal
Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.
Weighted Projective Spaces ML Description: The database of 5-vectors describing 4d weighted projective spaces which admit Calabi-Yau hypersurfaces are
Twin-deep neural network for semi-supervised learning of materials properties
Deep Semi-Supervised Teacher-Student Material Synthesizability Prediction Citation: Semi-supervised teacher-student deep neural network for materials
FinRLĀ-Meta: A Universe for DataĀ-Driven Financial Reinforcement Learning. š„
FinRL-Meta: A Universe of Market Environments. FinRL-Meta is a universe of market environments for data-driven financial reinforcement learning. Users
Centroid-UNet is deep neural network model to detect centroids from satellite images.
Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer
Semantically Contrastive Learning for Low-light Image Enhancement
Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity Introduction The 3D LiDAR place recognition aim
CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
This is the official repository of the paper: CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability A private copy of the
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
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 ā transcription factor binding
Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ā transc
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 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
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
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
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
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
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 | ē®ä½äøę 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
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
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 Moverās Distance Improves Out-Of-Distribution Face Identification
DeepFace-EMD: Re-ranking Using Patch-wise Earth Moverās 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 āThe Peril of Popular Deep Learning Uncertainty Estimation Methodsā
Uncertainty Estimation Methods Code for the paper āThe Peril of Popular Deep Learning Uncertainty Estimation Methodsā Reference If you use this code,
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
Experiments and examples converting Transformers to ONNX
Experiments and examples converting Transformers to ONNX This repository containes experiments and examples on converting different Transformers to ON
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
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
āāā VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain
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
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
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