5287 Repositories
Python robot-learning Libraries
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
code for Fast Point Cloud Registration with Optimal Transport
robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the
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-NewtonโA 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 ๐ 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
2021 Real Robot Challenge Phase2 attemp
Real_Robot_Challenge_Phase2_AE_attemp We(team name:thriftysnipe) are the first place winner of Phase1 in 2021 Real Robot Challenge. Please see this pa
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
A Lego Mindstorm robot for dealing out cards based on a birds-eye view of a poker table and given ArUco fiducial tags.
A Lego Mindstorm robot for dealing out cards based on a birds-eye view of a poker table and given ArUco fiducial tags.
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
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021]
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng
Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".
PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap
A large-scale database for graph representation learning
A large-scale database for graph representation learning
Machine Learning with JAX Tutorials
The purpose of this repo is to make it easy to get started with JAX. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning JAX.
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi
MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query
fMRIprep Pipeline To Machine Learning
fMRIprep Pipeline To Machine Learning(Demo) ๆๆ้ ็ฝฎๅๅจconfig.pyๆไปถไธๅฎไน ๅ็ฝฎ็ฏๅข(lilab) ๅไธช่็นๅๅฎ่ฃ docker๏ผๅนถๆfmripre็้ๅ ๅฏไปฅไฝฟ็จcondaไธญ็base็ฏๅข๏ผ็ธๅบ็็ฌฌไธไปฝๅ ไนๅๆดๆฐ๏ผ 1. fmriprep scr
This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation".
IR-GAIL This is an example implementation of the paper "Cross Domain Robot Imitation with Invariant Representation". Dependency The experiments are de
This repo represents all we learned and are learning in Data Structure course.
DataStructure Journey This repo represents all we learned and are learning in Data Structure course which is based on CLRS book and is being taught by
Decision Border Visualizer for Classification Algorithms
dbv Decision Border Visualizer for Classification Algorithms Project description A python package for Machine Learning Engineers who want to visualize
Code for "Discovering Non-monotonic Autoregressive Orderings with Variational Inference" (paper and code updated from ICLR 2021)
Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi
MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu
A Comprehensive Study on Learning-Based PE Malware Family Classification Methods
A Comprehensive Study on Learning-Based PE Malware Family Classification Methods Datasets Because of copyright issues, both the MalwareBazaar dataset
The command line interface for Gradient - Gradient is an an end-to-end MLOps platform
Gradient CLI Get started: Create Account โข Install CLI โข Tutorials โข Docs Resources: Website โข Blog โข Support โข Contact Sales Gradient is an an end-to
Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks
OnsagerNet Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks This is the original pyTorch implemenati
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN)
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).
Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested
A project that uses optical flow and machine learning to detect aimhacking in video clips.
waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che
Implementation for HFGI: High-Fidelity GAN Inversion for Image Attribute Editing
HFGI: High-Fidelity GAN Inversion for Image Attribute Editing High-Fidelity GAN Inversion for Image Attribute Editing Update: We released the inferenc
Generic image compressor for machine learning. Pytorch code for our paper "Lossy compression for lossless prediction".
Lossy Compression for Lossless Prediction Using: Training: This repostiory contains our implementation of the paper: Lossy Compression for Lossless Pr
[ICCV'21] Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (NeurIPS 2021)
VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
A complete end-to-end machine learning portal that covers processes starting from model training to the model predicting results using FastAPI.
Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes
Ralph is a command-line tool to fetch, extract, convert and push your tracking logs from various storage backends to your LRS or any other compatible storage or database backend.
Ralph is a command-line tool to fetch, extract, convert and push your tracking logs (aka learning events) from various storage backends to your
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
Robot to convert files to direct links, hosting files on Telegram servers, unlimited and without restrictions
stream-cloud demo : downloader_star_bot Run : Docker : install docker , docker-compose set Environment or edit Config/init.py docker-compose up Heroku
[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".
Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper โLear
Anderson Acceleration for Deep Learning
Anderson Accelerated Deep Learning (AADL) AADL is a Python package that implements the Anderson acceleration to speed-up the training of deep learning
Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide range of illumination variants of a single image.
Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Au
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
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layersโ.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.
Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl
Meta-Learning Sparse Implicit Neural Representations (NeurIPS 2021)
Meta-SparseINR Official PyTorch implementation of "Meta-learning Sparse Implicit Neural Representations" (NeurIPS 2021) by Jaeho Lee*, Jihoon Tack*, N
Node Dependent Local Smoothing for Scalable Graph Learning
Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04
A collection of Google research projects related to Federated Learning and Federated Analytics.
Federated Research Federated Research is a collection of research projects related to Federated Learning and Federated Analytics. Federated learning i
This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".
L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.
The codes of paper 'Active-LATHE: An Active Learning Algorithm for Boosting the Error exponent for Learning Homogeneous Ising Trees'
Active-LATHE: An Active Learning Algorithm for Boosting the Error exponent for Learning Homogeneous Ising Trees This project contains the codes of pap
The Official Implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose [NIPS 2021].
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The offical PyTorch implementation of Neural View Sy
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021) Video demo We here provide a video demo from co
This is the official implementation for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents" in NeurIPS 2021.
Observe then Incentivize Experiments This is the code used for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents",
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
TransMaS This repository is the official pytorch implementation of the following paper: NIPS2021 Mixed Supervised Object Detection by TransferringMask
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond
CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized
Learning where to learn - Gradient sparsity in meta and continual learning
Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co
[NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark
Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2
DreamerPro Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFl
Contrastive Learning with Non-Semantic Negatives
Contrastive Learning with Non-Semantic Negatives This repository is the official implementation of Robust Contrastive Learning Using Negative Samples
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili
Deep generative models of 3D grids for structure-based drug discovery
What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid
[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"
IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea
SimplEx - Explaining Latent Representations with a Corpus of Examples
SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbรฉ ([email protected]) This repository contains the imp
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
This repository is the official implementation of Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models Link to paper Abstract We study prediction of future out
RIM: Reliable Influence-based Active Learning on Graphs.
RIM: Reliable Influence-based Active Learning on Graphs. This repository is the official implementation of RIM. Requirements To install requirements:
Basic Docker Compose for Machine Learning Purposes
Docker-compose for Machine Learning How to use: cd docker-ml-jupyterlab
LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection.
LightLog Introduction LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection. Function description [BG
An inline real-time media searching robot without any database.
MediaBuddy A Telegram Inline media searching robot without any database. About mediaBuddy is an inline media searching robot. If you have so many movi
Repository for learning Python (Python Tutorial)
Repository for learning Python (Python Tutorial) Languages and Tools ๐งฐ Overview ๐ Repository for learning Python (Python Tutorial) Languages and Too
AgML is a comprehensive library for agricultural machine learning
AgML is a comprehensive library for agricultural machine learning. Currently, AgML provides access to a wealth of public agricultural datasets for common agricultural deep learning tasks.
โ๐๐ก๐ ๐๐จ๐ฌ๐ญ ๐๐จ๐ฐ๐๐ซ๐๐ฎ๐ฅ๐ฅ ๐๐ซ๐จ๐ฎ๐ฉ ๐๐๐ง๐๐ ๐๐ฆ๐๐ง๐ญ ๐๐จ๐ญโ
โ๐๐ก๐ ๐๐จ๐ฌ๐ญ ๐๐จ๐ฐ๐๐ซ๐๐ฎ๐ฅ๐ฅ ๐๐ซ๐จ๐ฎ๐ฉ ๐๐๐ง๐๐ ๐๐ฆ๐๐ง๐ญ ๐๐จ๐ญโ
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
A framework for attentive explainable deep learning on tabular data
๐ง kendrite A framework for attentive explainable deep learning on tabular data ๐จ Quick start kedro run ๐งฑ Built upon Technology Description Links ke
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.
Unbiased Learning To Rank Algorithms (ULTRA)
This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiments and research on learning to rank with human annotated or noisy labels.
Fast image augmentation library and an easy-to-use wrapper around other libraries
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
A booklet on machine learning systems design with exercises
Machine Learning Systems Design Read this booklet here. This booklet covers four main steps of designing a machine learning system: Project setup Data
Can a machine learning project be implemented to estimate the salaries of baseball players whose salary information and career statistics for 1986 are shared?
END TO END MACHINE LEARNING PROJECT ON HITTERS DATASET Can a machine learning project be implemented to estimate the salaries of baseball players whos
Implementing yolov4 target detection and tracking based on nao robot
Implementing yolov4 target detection and tracking based on nao robot
Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment
Preference-Planning-Deep-IRL Introduction Check my portfolio post Dependencies Gym stable-baselines3 PyTorch Usage Take Demonstration python3 record.
NLP - Machine learning
Flipkart-product-reviews NLP - Machine learning About Product reviews is an essential part of an online store like Flipkartโs branding and marketing.
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec
Cobra is a highly-accurate and lightweight voice activity detection (VAD) engine.
On-device voice activity detection (VAD) powered by deep learning.