5264 Repositories
Python reference-learning Libraries
Python package for reference counting native pointers
refcount master: testing: This package is primarily for managing resources in native libraries, written for instance in C++, from Python. While it boi
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.
B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).
RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc
Real-Time High-Resolution Background Matting
Real-Time High-Resolution Background Matting Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires captur
Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.
YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-
Deep Learning Based Fasion Recommendation System for Ecommerce
Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region. This repository provides the codebase and dataset for our work WORD: Revisiting Or
Perturb-and-max-product: Sampling and learning in discrete energy-based models
Perturb-and-max-product: Sampling and learning in discrete energy-based models This repo contains code for reproducing the results in the paper Pertur
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.
B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env
RLDS stands for Reinforcement Learning Datasets
RLDS RLDS stands for Reinforcement Learning Datasets and it is an ecosystem of tools to store, retrieve and manipulate episodic data in the context of
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2
3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A - Continual Learning Classification Challenge
Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay 3rd Place Solution for ICCV 2021 Workshop SS
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
A package for "Procedural Content Generation via Reinforcement Learning" OpenAI Gym interface.
Readme: Illuminating Diverse Neural Cellular Automata for Level Generation This is the codebase used to generate the results presented in the paper av
Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
OSCAR Project Page | Paper This repository contains the codebase used in OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Ma
Code for "Learning to Regrasp by Learning to Place"
Learning2Regrasp Learning to Regrasp by Learning to Place, CoRL 2021. Introduction We propose a point-cloud-based system for robots to predict a seque
Adversarial Graph Augmentation to Improve Graph Contrastive Learning
ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang
On-device speech-to-index engine powered by deep learning.
On-device speech-to-index engine powered by deep learning.
Traingenerator 🧙 A web app to generate template code for machine learning ✨
Traingenerator 🧙 A web app to generate template code for machine learning ✨ 🎉 Traingenerator is now live! 🎉
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.
AbelNN: Deep Learning Python module from scratch
AbelNN: Deep Learning Python module from scratch I have implemented several neural networks from scratch using only Numpy. I have designed the module
Test symmetries with sklearn decision tree models
Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro
Tools for Optuna, MLflow and the integration of both.
HPOflow - Sphinx DOC Tools for Optuna, MLflow and the integration of both. Detailed documentation with examples can be found here: Sphinx DOC Table of
Tool which allow you to detect and translate text.
Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr
A Python 3.6+ package to run .many files, where many programs written in many languages may exist in one file.
RunMany Intro | Installation | VSCode Extension | Usage | Syntax | Settings | About A tool to run many programs written in many languages from one fil
This is a text summarizing tool written in Python
Summarize Written by: Ling Li Ya This is a text summarizing tool written in Python. User Guide Some things to note: The application is accessible here
A learning-based data collection tool for human segmentation
FullBodyFilter A Learning-Based Data Collection Tool For Human Segmentation Contents Documentation Source Code and Scripts Overview of Project Usage O
Learning-based agent for Google Research Football
TiKick 1.Introduction Learning-based agent for Google Research Football Code accompanying the paper "TiKick: Towards Playing Multi-agent Football Full
Code for "Learning Graph Cellular Automata"
Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec
Deep-learning X-Ray Micro-CT image enhancement, pore-network modelling and continuum modelling
EDSR modelling A Github repository for deep-learning image enhancement, pore-network and continuum modelling from X-Ray Micro-CT images. The repositor
Deep Learning Algorithms for Hedging with Frictions
Deep Learning Algorithms for Hedging with Frictions This repository contains the Forward-Backward Stochastic Differential Equation (FBSDE) solver and
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs
Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy
Source Code for ICSE 2022 Paper - ``Can We Achieve Fairness Using Semi-Supervised Learning?''
Fair-SSL Source Code for ICSE 2022 Paper - Can We Achieve Fairness Using Semi-Supervised Learning? Ethical bias in machine learning models has become
An Open-Source Toolkit for Prompt-Learning.
An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context
Code for NeurIPS 2021 paper "Curriculum Offline Imitation Learning"
README The code is based on the ILswiss. To run the code, use python run_experiment.py --nosrun -e your YAML file -g gpu id Generally, run_experim
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
causal-bald | Abstract | Installation | Example | Citation | Reproducing Results DUE An implementation of the methods presented in Causal-BALD: Deep B
Official implementation of "Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention" (BMVC 2021).
Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require
Code for ICMI2020 and ICMI2021 papers: "Studying Person-Specific Pointing and Gaze Behavior for Multimodal Referencing of Outside Objects from a Moving Vehicle" and "ML-PersRef: A Machine Learning-based Personalized Multimodal Fusion Approach for Referencing Outside Objects From a Moving Vehicle"
ML-PersRef This repository has python code (in jupyter notebooks) for both of the following papers: ML-PersRef: A Machine Learning-based Personalized
Geometric Algebra package for JAX
JAXGA - JAX Geometric Algebra GitHub | Docs JAXGA is a Geometric Algebra package on top of JAX. It can handle high dimensional algebras by storing onl
Machine Learning approach for quantifying detector distortion fields
DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model
[NeurIPS 2021] Code for Unsupervised Learning of Compositional Energy Concepts
Unsupervised Learning of Compositional Energy Concepts This is the pytorch code for the paper Unsupervised Learning of Compositional Energy Concepts.
A visualisation tool for Deep Reinforcement Learning
DRLVIS - Visualising Deep Reinforcement Learning Created by Marios Sirtmatsis with the support of Alex Bäuerle. DRLVis is an application used for visu
Automatic deep learning for image classification.
AutoDL AutoDL automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few line
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
A python library for highly configurable transformers - easing model architecture search and experimentation.
A python library for highly configurable transformers - easing model architecture search and experimentation.
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021
PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin
[NeurIPS 2021] PyTorch Code for Accelerating Robotic Reinforcement Learning with Parameterized Action Primitives
Robot Action Primitives (RAPS) This repository is the official implementation of Accelerating Robotic Reinforcement Learning via Parameterized Action
JORLDY an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise
Repository for Open Source Reinforcement Learning Framework JORLDY
Active Learning demo using two small datasets
ActiveLearningDemo How to run step one put the dataset folder and use command below to split the dataset to the required structure run utils.py For ea
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation (CoRL 2021)
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation [Project website] [Paper] This project is a PyTorch i
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just
This library is testing the ethics of language models by using natural adversarial texts.
prompt2slip This library is testing the ethics of language models by using natural adversarial texts. This tool allows for short and simple code and v
The spiritual successor to knockknock for PyTorch Lightning, get notified when your training ends
Who's there? The spiritual successor to knockknock for PyTorch Lightning, to get a notification when your training is complete or when it crashes duri
iris - Open Source Photos Platform Powered by PyTorch
Open Source Photos Platform Powered by PyTorch. Submission for PyTorch Annual Hackathon 2021.
Official implementation of Generalized Data Weighting via Class-level Gradient Manipulation (NeurIPS 2021).
Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas
An efficient and easy-to-use deep learning model compression framework
TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
Data science, Data manipulation and Machine learning package.
duality Data science, Data manipulation and Machine learning package. Use permitted according to the terms of use and conditions set by the attached l
Source code of the paper Meta-learning with an Adaptive Task Scheduler.
ATS About Source code of the paper Meta-learning with an Adaptive Task Scheduler. If you find this repository useful in your research, please cite the
Implementing DeepMind's Fast Reinforcement Learning paper
Fast Reinforcement Learning This is a repo where I implement the algorithms in the paper, Fast reinforcement learning with generalized policy updates.
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable.
SDK: Overview of the Kubeflow pipelines service Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on
Some methods for comparing network representations in deep learning and neuroscience.
Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation
DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning
PECOS - Prediction for Enormous and Correlated Spaces
PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i
Generalized Data Weighting via Class-level Gradient Manipulation
Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas
Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided curriculum Learning Approach
Get Fooled for the Right Reason Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness throu
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models
DSEE Codes for [Preprint] DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Ch
Generalized and Efficient Blackbox Optimization System.
OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio
Revealing and Protecting Labels in Distributed Training
Revealing and Protecting Labels in Distributed Training
FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.
FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.
SW components and demos for visual kinship recognition. An emphasis is put on the FIW dataset-- data loaders, benchmarks, results in summary.
FIW Data Development Kit Table of Contents Introduction Families In the Wild Database Publications Organization To Do License Getting Involved Introdu
[NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”
Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in
gtfs2vec - Learning GTFS Embeddings for comparing PublicTransport Offer in Microregions
gtfs2vec This is a companion repository for a gtfs2vec - Learning GTFS Embeddings for comparing PublicTransport Offer in Microregions publication. Vis
Evaluating deep transfer learning for whole-brain cognitive decoding
Evaluating deep transfer learning for whole-brain cognitive decoding This README file contains the following sections: Project description Repository
This repository contains a PyTorch implementation of the paper Learning to Assimilate in Chaotic Dynamical Systems.
Amortized Assimilation This repository contains a PyTorch implementation of the paper Learning to Assimilate in Chaotic Dynamical Systems. Abstract: T
This is the repository for Learning to Generate Piano Music With Sustain Pedals
SusPedal-Gen This is the official repository of Learning to Generate Piano Music With Sustain Pedals Demo Page Dataset The dataset used in this projec
Corruption Invariant Learning for Re-identification
Corruption Invariant Learning for Re-identification The official repository for Benchmarks for Corruption Invariant Person Re-identification (NeurIPS
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed
Implicit Model Specialization through DAG-based Decentralized Federated Learning
Federated Learning DAG Experiments This repository contains software artifacts to reproduce the experiments presented in the Middleware '21 paper "Imp
Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotlight)
Mixture Proportion Estimation and PU Learning: A Modern Approach This repository is the official implementation of Mixture Proportion Estimation and P
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.
Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021
PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.
Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil
Companion repository to the paper accepted at the 4th ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities
Transfer learning approach to bicycle sharing systems station location planning using OpenStreetMap Companion repository to the paper accepted at the
Migration of Edge-based Distributed Federated Learning
FedFly: Towards Migration in Edge-based Distributed Federated Learning About the research Due to mobility, a device participating in Federated Learnin
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation
Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation Introduction 📋 Official implementation of Explainable Robust Learnin
Companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsura et al.
META-RS This is the companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsu
A denoising diffusion probabilistic model synthesises galaxies that are qualitatively and physically indistinguishable from the real thing.
Realistic galaxy simulation via score-based generative models Official code for 'Realistic galaxy simulation via score-based generative models'. We us
Matplotlib Image labeller for classifying images
mpl-image-labeller Use Matplotlib to label images for classification. Works anywhere Matplotlib does - from the notebook to a standalone gui! For more
This is an auto-ML tool specialized in detecting of outliers
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectrum sensing.
Deep-Learning-based-Spectrum-Sensing Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectru
Implementation for paper "Towards the Generalization of Contrastive Self-Supervised Learning"
Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi
The Simpsons and Machine Learning: What makes an Episode Great?
The Simpsons and Machine Learning: What makes an Episode Great? Check out my Medium article on this! PROBLEM: The Simpsons has had a decline in qualit
Unofficial implementation of the paper: PonderNet: Learning to Ponder in TensorFlow
PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:
PyTorch implementation of UPFlow (unsupervised optical flow learning)
UPFlow: Upsampling Pyramid for Unsupervised Optical Flow Learning By Kunming Luo, Chuan Wang, Shuaicheng Liu, Haoqiang Fan, Jue Wang, Jian Sun Megvii