6089 Repositories
Python Federated-Learning-Framework Libraries
Job-Recommend-Competition - Vectorwise Interpretable Attentions for Multimodal Tabular Data
SiD - Simple Deep Model Vectorwise Interpretable Attentions for Multimodal Tabul
Kroomsa: A search engine for the curious
Kroomsa A search engine for the curious. It is a search algorithm designed to en
Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity
Product-based-recommendation-system A product based recommendation system which
Breaching - Breaching privacy in federated learning scenarios for vision and text
Breaching - A Framework for Attacks against Privacy in Federated Learning This P
Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser
Federated_Learning š» This projest include common test models for federated lear
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss
"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i
MOT-Tracking-by-Detection-Pipeline - For Tracking-by-Detection format MOT (Multi Object Tracking), is it a framework that separates Detection and Tracking processes?
MOT-Tracking-by-Detection-Pipeline Tracking-by-Detectionå½¢å¼ć®MOT(Multi Object Trac
LotteryBuyPredictionWebApp - Lottery Purchase Prediction Model
Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization
Text-Summarization-using-NLP Text Summarization using NLP to fetch BBC News Arti
SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022
SafePicking Learning Safe Object Extraction via Object-Level Mapping Kentaro Wad
Python-samples - This project is to help someone need some practices when learning python language
Python-samples - This project is to help someone need some practices when learning python language
FAMIE is a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction (IE)
FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.
OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble
Wordle RL The aim of this project is to build an AI bot that can play the Wordle game, or more generally Squabble I know there are more deterministic
Detecting drunk people through thermal images using Deep Learning (CNN)
Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd
A lossless neural compression framework built on top of JAX.
Kompressor Branch CI Coverage main (active) main development A neural compression framework built on top of JAX. Install setup.py assumes a compatible
The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory
This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the
A small module to communicate with Triller's API
A small, UNOFFICIAL module to communicate with Triller's API. I plan to add more features/methods in the future.
An ascii art generator that's actually good. Does edge detection and selects the most appropriate characters.
Ascii Artist An ascii art generator that's actually good. Does edge detection and selects the most appropriate characters. Installing Installing with
The visual framework is designed on the idea of module and implemented by mixin method
Visual Framework The visual framework is designed on the idea of module and implemented by mixin method. Its biggest feature is the mixins module whic
Apk Framework Detector
šššProgram helps you to detect the major framework or technology used in writing any android app. Just provide the apk šš
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM, XGBoost, Ranger...).
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Introduction OpenFed is a foundational library for federated learning
MVSDF - Learning Signed Distance Field for Multi-view Surface Reconstruction
MVSDF - Learning Signed Distance Field for Multi-view Surface Reconstruction This is the official implementation for the ICCV 2021 paper Learning Sign
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data"
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data" You can download the pretrained
GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery This is the code to the paper: Gradient-Based Learn
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL)
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL) A preprint version of our paper: Link here This is a samp
This repository contains the source code of Auto-Lambda and baselines from the paper, Auto-Lambda: Disentangling Dynamic Task Relationships.
Auto-Lambda This repository contains the source code of Auto-Lambda and baselines from the paper, Auto-Lambda: Disentangling Dynamic Task Relationship
PyTorch implementation of the Crafting Better Contrastive Views for Siamese Representation Learning
Crafting Better Contrastive Views for Siamese Representation Learning This is the official PyTorch implementation of the ContrastiveCrop paper: @artic
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors āāIn order to facilitate the res
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences This repository is an official PyTorch implementation of Neighbor
Using deep learning model to detect breast cancer.
Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas
PyTorch implementation of NATSpeech: A Non-Autoregressive Text-to-Speech Framework
A Non-Autoregressive Text-to-Speech (NAR-TTS) framework, including official PyTorch implementation of PortaSpeech (NeurIPS 2021) and DiffSpeech (AAAI 2022)
Lseng-iseng eksplor Machine Learning dengan menggunakan library Scikit-Learn
Kalo dengar istilah ML, biasanya rada ambigu. Soalnya punya beberapa kepanjangan, seperti Mobile Legend, Makan Lontong, Ma**ng L*v* dan lain-lain. Tapi pada repo ini membahas Machine Learning :)
Vaex library for Big Data Analytics of an Airline dataset
Vaex-Big-Data-Analytics-for-Airline-data A Python notebook (ipynb) created in Jupyter Notebook, which utilizes the Vaex library for Big Data Analytics
Automatic game data translator for RPGMaker-MV
RPGMaker-MV Translator š¹ļø š® Use AI to translate all the dialogs and texts of your RPGMaker automatically. š You worked hard to make your game, now
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.
AllSet This is the repo for our paper: You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. We prepared all codes and a subse
Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"
Learning to Bootstrap for Combating Label Noise This repo is the official implementation of our paper "Learning to Bootstrap for Combating Label Noise
Learning Synthetic Environments and Reward Networks for Reinforcement Learning
Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (
Learning Features with Parameter-Free Layers, ICLR 2022
Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning
BEAS Blockchain Enabled Asynchronous and Secure Federated Machine Learning Default Network Configuration: The default application uses the HyperLedger
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion
MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular
LyaNet: A Lyapunov Framework for Training Neural ODEs
LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations
Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
Transfer Learning Remote Sensing
Transfer_Learning_Remote_Sensing Simulation R codes for data generation and visualizations are in the folder simulation. Experiment: California Housin
LightGBM + Optuna: no brainer
AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin
A type based dependency injection framework for Python 3.9+
Alluka A type based dependency injection framework for Python 3.9+. Installation You can install Alluka from PyPI using the following command in any P
PyTorch implementation for NCL (Neighborhood-enrighed Contrastive Learning)
NCL (Neighborhood-enrighed Contrastive Learning) This is the official PyTorch implementation for the paper: Zihan Lin*, Changxin Tian*, Yupeng Hou* Wa
Clean and readable code for Decision Transformer: Reinforcement Learning via Sequence Modeling
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
Image-to-image regression with uncertainty quantification in PyTorch
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
A Broad Study on the Transferability of Visual Representations with Contrastive Learning This repository contains code for the paper: A Broad Study on
Learning Visual Words for Weakly-Supervised Semantic Segmentation
[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup
Causal Influence Detection for Improving Efficiency in Reinforcement Learning
Causal Influence Detection for Improving Efficiency in Reinforcement Learning This repository contains the code release for the paper "Causal Influenc
Supplementary Data for Evolving Reinforcement Learning Algorithms
evolvingrl Supplementary Data for Evolving Reinforcement Learning Algorithms This dataset contains 1000 loss graphs from two experiments: 500 unique g
CATE: Computation-aware Neural Architecture Encoding with Transformers
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.
Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection?
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
A framework for GPU based high-performance medical image processing and visualization
FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c
Learning Features with Parameter-Free Layers (ICLR 2022)
Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up
SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers
SAGE: Sensitivity-guided Adaptive Learning Rate for Transformers This repo contains our codes for the paper "No Parameters Left Behind: Sensitivity Gu
A simple machine learning python sign language detection project.
SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri
GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.
GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp
PICO is an algorithm for exploiting Reinforcement Learning (RL) on Multi-agent Path Finding tasks.
PICO is an algorithm for exploiting Reinforcement Learning (RL) on Multi-agent Path Finding tasks. It is developed by the Multi-Agent Artificial Intel
Learning Efficient Online 3D Bin Packing on Packing Configuration Trees
Learning Efficient Online 3D Bin Packing on Packing Configuration Trees This repository is being continuously updated, please stay tunedļ¼ Any code con
To build a regression model to predict the concrete compressive strength based on the different features in the training data.
Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features
Implementation of SOMs (Self-Organizing Maps) with neighborhood-based map topologies.
py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records
HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro
Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.
Using Data Science with Machine Learning techniques (ETL pipeline and ML pipeline) to classify received messages after disasters.
PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams
PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams Motivation When dataset freshness is critical, the annotating of high speed
Supervised Contrastive Learning for Product Matching
Contrastive Product Matching This repository contains the code and data download links to reproduce the experiments of the paper "Supervised Contrasti
Computational inteligence project on faces in the wild dataset
Table of Contents The general idea How these scripts work? Loading data Needed modules and global variables Parsing the arrays in dataset Extracting a
This repository contains examples of Task-Informed Meta-Learning
Task-Informed Meta-Learning This repository contains examples of Task-Informed Meta-Learning (paper). We consider two tasks: Crop Type Classification
PyTorch implementation of SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I
NeuroGen: activation optimized image synthesis for discovery neuroscience
NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image;
Deep Surface Reconstruction from Point Clouds with Visibility Information
Data, code and pretrained models for the paper Deep Surface Reconstruction from Point Clouds with Visibility Information.
CLASSIX is a fast and explainable clustering algorithm based on sorting
CLASSIX Fast and explainable clustering based on sorting CLASSIX is a fast and explainable clustering algorithm based on sorting. Here are a few highl
Course materials for a 3-day seminar "Machine Learning and NLP: Advances and Applications" at New College of Florida
Machine Learning and NLP: Advances and Applications This repository hosts the course materials used for a 3-day seminar "Machine Learning and NLP: Adv
Vertex AI: Serverless framework for MLOPs (ESP / ENG)
Vertex AI: Serverless framework for MLOPs (ESP / ENG) EspaƱol QuƩ es esto? Este repo contiene un pipeline end to end diseƱado usando el SDK de Kubeflo
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg
Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates"
Peer Loss functions This repository is the (Multi-Class & Deep Learning) Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels wi
Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2.
Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2. It is trained (finetuned) on a curated list of approximately 45K Python (~470MB) files gathered from the Github. Currently, it just works properly on Python but not bad at other languages (thanks to GPT-2's power).
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
Volumetric TSDF Fusion of RGB-D Images in Python This is a lightweight python script that fuses multiple registered color and depth images into a proj
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
The pyrelational package offers a flexible workflow to enable active learning with as little change to the models and datasets as possible
pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.
Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python
deepface Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid
The proliferation of disinformation across social media has led the application of deep learning techniques to detect fake news.
Fake News Detection Overview The proliferation of disinformation across social media has led the application of deep learning techniques to detect fak
A Graph Learning library for Humans
A Graph Learning library for Humans These novel algorithms include but are not limited to: A graph construction and graph searching class can be found