7552 Repositories
Python Deep-Learning-Based-State-Estimation Libraries
Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports
Recurrent Conditional Query Learning
Recurrent Conditional Query Learning (RCQL) This repository contains the Pytorch implementation of One Model Packs Thousands of Items with Recurrent C
Low-dose Digital Mammography with Deep Learning
Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography ====== This repository contains
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li
Stochastic gradient descent with model building
Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi
PyTorch implementation of MulMON
MulMON This repository contains a PyTorch implementation of the paper: Learning Object-Centric Representations of Multi-object Scenes from Multiple Vi
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"
Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and
Improving Compound Activity Classification via Deep Transfer and Representation Learning
Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions Kapoutsis, A.C., Chatzichristofis,
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is
Codebase for the paper titled "Continual learning with local module selection"
This repository contains the codebase for the paper Continual Learning via Local Module Composition. Setting up the environemnt Create a new conda env
Implementation of the paper Scalable Intervention Target Estimation in Linear Models (NeurIPS 2021), and the code to generate simulation results.
Scalable Intervention Target Estimation in Linear Models Implementation of the paper Scalable Intervention Target Estimation in Linear Models (NeurIPS
MRI reconstruction (e.g., QSM) using deep learning methods
deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later
Learning to Map Large-scale Sparse Graphs on Memristive Crossbar
Release of AutoGMap:Learning to Map Large-scale Sparse Graphs on Memristive Crossbar For reproduction of our searched model, the Ubuntu OS is recommen
Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information"
Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information" Notes I probabl
Code base for reproducing results of I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS (2021)
Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin
Large-scale Hyperspectral Image Clustering Using Contrastive Learning, CIKM 21 Workshop
Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri
Solving Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge
Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge Associated code for the paper Zero-Shot Learning in Named Entity Recognitio
Code-free deep segmentation for computational pathology
NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation
On Effective Scheduling of Model-based Reinforcement Learning
On Effective Scheduling of Model-based Reinforcement Learning Code to reproduce the experiments in On Effective Scheduling of Model-based Reinforcemen
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as
Point detection through multi-instance deep heatmap regression for sutures in endoscopy
Suture detection PyTorch This repo contains the reference implementation of suture detection model in PyTorch for the paper Point detection through mu
Predict halo masses from simulations via graph neural networks
HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati
Source code for paper "Deep Diffusion Models for Robust Channel Estimation", TBA.
diffusion-channels Source code for paper "Deep Diffusion Models for Robust Channel Estimation". Generic flow: Use 'matlab/main.mat' to generate traini
Learning a mapping from images to psychological similarity spaces with neural networks.
LearningPsychologicalSpaces v0.1: v1.1: v1.2: v1.3: v1.4: v1.5: The code in this repository explores learning a mapping from images to psychological s
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
Next-gen Rowhammer fuzzer that uses non-uniform, frequency-based patterns.
Blacksmith Rowhammer Fuzzer This repository provides the code accompanying the paper Blacksmith: Scalable Rowhammering in the Frequency Domain that is
Official implementation of Meta-StyleSpeech and StyleSpeech
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code
RRxIO - Robust Radar Visual/Thermal Inertial Odometry: Robust and accurate state estimation even in challenging visual conditions.
RRxIO - Robust Radar Visual/Thermal Inertial Odometry RRxIO offers robust and accurate state estimation even in challenging visual conditions. RRxIO c
PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"
Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning PyTorch code for the ICCV 2021 paper: Always Be Dreaming: A New Approach f
This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming"
Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig
Learning Temporal Consistency for Low Light Video Enhancement from Single Images (CVPR2021)
StableLLVE This is a Pytorch implementation of "Learning Temporal Consistency for Low Light Video Enhancement from Single Images" in CVPR 2021, by Fan
Code accompanying the paper "Knowledge Base Completion Meets Transfer Learning"
Knowledge Base Completion Meets Transfer Learning This code accompanies the paper Knowledge Base Completion Meets Transfer Learning published at EMNLP
This Project is based on NLTK It generates a RANDOM WORD from a predefined list of words, From that random word it read out the word, its meaning with parts of speech , its antonyms, its synonyms
This Project is based on NLTK(Natural Language Toolkit) It generates a RANDOM WORD from a predefined list of words, From that random word it read out the word, its meaning with parts of speech , its antonyms, its synonyms
A collection of online resources to help you on your Tech journey.
Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di
SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning
SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode
kitty - the fast, feature-rich, cross-platform, GPU based terminal
kitty - the fast, feature-rich, cross-platform, GPU based terminal
Fully Dockerized cryptocurrencies Trading Bot, based on Freqtrade engine. Multi instances.
Cryptocurrencies Trading Bot - Freqtrade Manager This automated Trading Bot is based on the amazing Freqtrade one. It allows you to manage many Freqtr
Mobile based API for Crunchyroll BETA (and Downloader).
Mobile based API for Crunchyroll BETA (and Downloader). Not restricted on servers and NO CLOUDFLARE
A python script that changes your desktop background based on current weather and time of the day.
Desktop background wallpaper, based on current weather and time A python script that changes your computer's desktop background based on current weath
An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv
FisherPruning-Pytorch An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv Main Functions Pruning f
A Gtk based Image Selector with Preview
gtk-image-selector This is an attempt to restore Gtk Image Chooser "lost functionality": displaying an image preview when selecting images... This is
`rosbag filter` with Gooey-based GUI
rosbag_filter_gui rosbag filter with Gooey-based GUI Test-passed Ubuntu 20.04 ROS Noetic Python 3.8 Installation
A "finish the lyrics" game using Spotify, YouTube Transcript, and YouTube Search APIs, coupled with visual machine learning
Singify Introducing Singify, the party game! Challenge your friend to who knows songs better. Play random songs from your very own Spotify playlist an
Task-related Saliency Network For Few-shot learning
Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo
Optimal space decomposition based-product quantization for approximate nearest neighbor search
Optimal space decomposition based-product quantization for approximate nearest neighbor search Abstract Product quantization(PQ) is an effective neare
Python-based proof-of-concept tool for generating payloads that utilize unsafe Java object deserialization.
Python-based proof-of-concept tool for generating payloads that utilize unsafe Java object deserialization.
MMFlow is an open source optical flow toolbox based on PyTorch
Documentation: https://mmflow.readthedocs.io/ Introduction English | 简体中文 MMFlow is an open source optical flow toolbox based on PyTorch. It is a part
Service for working with open data of the State Duma of the Russian Federation
Сервис для работы с открытыми данными Госдумы РФ Исходные данные из API Госдумы РФ извлекаются с помощью Apache Nifi и приземляются в хранилище Clickh
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module
sktime companion package for deep learning based on TensorFlow
NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and
Time Series Cross-Validation -- an extension for scikit-learn
TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini
Statistical and Algorithmic Investing Strategies for Everyone
Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic
scikit-survival is a Python module for survival analysis built on top of scikit-learn.
scikit-survival scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizi
PySurvival is an open source python package for Survival Analysis modeling
PySurvival What is Pysurvival ? PySurvival is an open source python package for Survival Analysis modeling - the modeling concept used to analyze or p
Deep Survival Machines - Fully Parametric Survival Regression
Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
pymc-learn: Practical Probabilistic Machine Learning in Python
pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc
Responsible Machine Learning with Python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice,
LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.
Python package to visualize and cluster partial dependence.
partial_dependence A python library for plotting partial dependence patterns of machine learning classifiers. The technique is a black box approach to
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
Responsible Machine Learning With Great Power Comes Great Responsibility. Voltaire (well, maybe) How to develop machine learning models in a responsib
XAI - An eXplainability toolbox for machine learning
XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai
moDel Agnostic Language for Exploration and eXplanation
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
Fit interpretable models. Explain blackbox machine learning.
InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Provide an input CSV and a target field to predict, generate a model + code to run it.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
Neural Architecture Search Powered by Swarm Intelligence 🐜
Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle
A hyperparameter optimization framework
Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software
🌊 River is a Python library for online machine learning.
River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on streaming data.
onelearn: Online learning in Python
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
Transform ML models into a native code with zero dependencies
m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects
Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow
A collection of video resources for machine learning
Machine Learning Videos This is a collection of recorded talks at machine learning conferences, workshops, seminars, summer schools, and miscellaneous
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
YOLOX_AUDIO is an audio event detection model based on YOLOX
YOLOX_AUDIO is an audio event detection model based on YOLOX, an anchor-free version of YOLO. This repo is an implementated by PyTorch. Main goal of YOLOX_AUDIO is to detect and classify pre-defined audio events in multi-spectrogram domain using image object detection frameworks.
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)
GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler
A CV toolkit for my papers.
PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to
reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
UPSNet: A Unified Panoptic Segmentation Network
UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te
BiSeNet based on pytorch
BiSeNet BiSeNet based on pytorch 0.4.1 and python 3.6 Dataset Download CamVid dataset from Google Drive or Baidu Yun(6xw4). Pretrained model Download
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation This implementation is based on orobix implement
Understanding Convolution for Semantic Segmentation
TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)
Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel
Real-time Joint Semantic Reasoning for Autonomous Driving
MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-
Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"
Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo