5920 Repositories
Python Traffic-Signs-Recognition-Machine-Learning Libraries
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:
Face recognition with trained classifiers for detecting objects using OpenCV
Face_Detector Face recognition with trained classifiers for detecting objects using OpenCV Libraries required to be installed using pip Command: cv2 n
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
Repository for learning Python (Python Tutorial)
Repository for learning Python (Python Tutorial) Languages and Tools 🧰 Overview 📑 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.
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
🧠 kendrite A framework for attentive explainable deep learning on tabular data 💨 Quick start kedro run 🧱 Built upon Technology Description Links ke
This is a GUI for scrapping PDFs with the help of optical character recognition making easier than ever to scrape PDFs.
pdf-scraper-with-ocr With this tool I am aiming to facilitate the work of those who need to scrape PDFs either by hand or using tools that doesn't imp
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
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.
Image Recognition using Pytorch
PyTorch Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot practice and contributing in
NLP - Machine learning
Flipkart-product-reviews NLP - Machine learning About Product reviews is an essential part of an online store like Flipkart’s branding and marketing.
The PyTorch based implementation of continuous integrate-and-fire (CIF) module.
CIF-PyTorch This is a PyTorch based implementation of continuous integrate-and-fire (CIF) module for end-to-end (E2E) automatic speech recognition (AS
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.
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator
DRL-robot-navigation Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gra
Unsupervised intent recognition
INTENT author: steeve LAQUITAINE description: deployment pattern: currently batch only Setup & run git clone https://github.com/slq0/intent.git bash
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
Intrusion Detection System using ensemble learning (machine learning)
IDS-ML implementation of an intrusion detection system using ensemble machine learning methods Data set This project is carried out using the UNSW-15
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
AugMax: Adversarial Composition of Random Augmentations for Robust Training
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
A tensorflow model that predicts if the image is of a cat or of a dog.
Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
The Unsupervised Reinforcement Learning Benchmark (URLB)
The Unsupervised Reinforcement Learning Benchmark (URLB) URLB provides a set of leading algorithms for unsupervised reinforcement learning where agent
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
keyframes-CNN-RNN(action recognition)
keyframes-CNN-RNN(action recognition) Environment: python=3.7 pytorch=1.2 Datasets: Following the format of UCF101 action recognition. Run steps: Mo
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images (ISBI 2021, MELBA 2021)
MultiMix This repository contains the implementation of MultiMix. Our publications for this project are listed below: "MultiMix: Sparingly Supervised,
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earth’s Mantle Convection data set be built such that it can be readily run in
Code Release for the paper "TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation"
TriBERT This repository contains the code for the NeurIPS 2021 paper titled "TriBERT: Full-body Human-centric Audio-visual Representation Learning for
PyTorch code accompanying the paper "Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning" (NeurIPS 2021).
HIGL This is a PyTorch implementation for our paper: Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning (NeurIPS 2021). Our cod
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning Reference Abeßer, J. & Müller, M. Towards Audio Domain Adapt
Audio Visual Emotion Recognition using TDA
Audio Visual Emotion Recognition using TDA RAVDESS database with two datasets analyzed: Video and Audio dataset: Audio-Dataset: https://www.kaggle.com
A Closer Look at Reference Learning for Fourier Phase Retrieval
A Closer Look at Reference Learning for Fourier Phase Retrieval This repository contains code for our NeurIPS 2021 Workshop on Deep Learning and Inver
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
Diverse Object-Scene Compositions For Zero-Shot Action Recognition
Diverse Object-Scene Compositions For Zero-Shot Action Recognition This repository contains the source code for the use of object-scene compositions f
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch.
The SpeechBrain Toolkit SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch. The goal is to create a single, flexible, and us
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Official implementation of "FL-WBC: Enhan
Repository for Driving Style Recognition algorithms for Autonomous Vehicles
Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making Created by Iago Pachêco Gomes at USP - ICM
Code for our paper: Online Variational Filtering and Parameter Learning
Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild Akash Sengupta, Ignas Budvytis, Robert
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
This repository contains the implementation of the paper: "Towards Frequency-Based Explanation for Robust CNN"
RobustFreqCNN About This repository contains the implementation of the paper "Towards Frequency-Based Explanation for Robust CNN" arxiv. It primarly d
An implementation for the loss function proposed in Decoupled Contrastive Loss paper.
Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P
Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)
Introduction This repository contains my unofficial reimplementation of the standard ECAPA-TDNN, which is the speaker recognition in VoxCeleb2 dataset
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
Create and implement a deep learning library from scratch.
In this project, we create and implement a deep learning library from scratch. Table of Contents Deep Leaning Library Table of Contents About The Proj
JAXDL: JAX (Flax) Deep Learning Library
JAXDL: JAX (Flax) Deep Learning Library Simple and clean JAX/Flax deep learning algorithm implementations: Soft-Actor-Critic (arXiv:1812.05905) Transf
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify
A PyTorch Lightning Callback for pushing models to the Hugging Face Hub 🤗⚡️
hf-hub-lightning A callback for pushing lightning models to the Hugging Face Hub. Note: I made this package for myself, mostly...if folks seem to be i
Machine Translation Implement By Bi-GRU And Transformer
Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be
PyTorch implementation of "A Simple Baseline for Low-Budget Active Learning".
A Simple Baseline for Low-Budget Active Learning This repository is the implementation of A Simple Baseline for Low-Budget Active Learning. In this pa
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
A lightweight python AUTOmatic-arRAY library.
A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.
Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression
Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx
PyTorch implementation of SmoothGrad: removing noise by adding noise.
SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro
Anuvada: Interpretable Models for NLP using PyTorch
Anuvada: Interpretable Models for NLP using PyTorch So, you want to know why your classifier arrived at a particular decision or why your flashy new d
Improving Calibration for Long-Tailed Recognition (CVPR2021)
MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
A method for cleaning and classifying text using transformers.
NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data
Simple Machine Learning Tool Kit
Getting started smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during data preparation testing your model The g
Deep learning image registration library for PyTorch
TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)
Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification
Deep Learning for Computer Vision final project
Deep Learning for Computer Vision final project
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Anti-Backdoor learning (NeurIPS 2021)
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. The Anti-Backdoor Learning
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"
Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
Instance-Dependent Partial Label Learning
Instance-Dependent Partial Label Learning Installation pip install -r requirements.txt Run the Demo benchmark-random mnist python -u main.py --gpu 0 -
Learning-Augmented Dynamic Power Management
Learning-Augmented Dynamic Power Management This repository contains source code accompanying paper Learning-Augmented Dynamic Power Management with M
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai
Code for "AutoMTL: A Programming Framework for Automated Multi-Task Learning"
AutoMTL: A Programming Framework for Automated Multi-Task Learning This is the website for our paper "AutoMTL: A Programming Framework for Automated M