5436 Repositories
Python adversarial-learning Libraries
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat
Reinforcement Learning Theory Book (rus)
Reinforcement Learning Theory Book (rus)
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
Readme File for "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" by Ham, Imai, and Janson. (2022) All scripts were written and
This repository contains the implementation of the HealthGen model, a generative model to synthesize realistic EHR time series data with missingness
HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize
MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios
MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios This is the official TensorFlow implementation of MetaTTE in the
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters
CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt
GAN-based Matrix Factorization for Recommender Systems
GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res
DROPO: Sim-to-Real Transfer with Offline Domain Randomization
DROPO: Sim-to-Real Transfer with Offline Domain Randomization Gabriele Tiboni, Karol Arndt, Ville Kyrki. This repository contains the code for the pap
A deep learning framework for historical document image analysis
DIVA-DAF Description A deep learning framework for historical document image analysis. How to run Install dependencies # clone project git clone https
A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation".
Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y
Distance-Ratio-Based Formulation for Metric Learning
Distance-Ratio-Based Formulation for Metric Learning Environment Python3 Pytorch (http://pytorch.org/) (version 1.6.0+cu101) json tqdm Preparing datas
On the adaptation of recurrent neural networks for system identification
On the adaptation of recurrent neural networks for system identification This repository contains the Python code to reproduce the results of the pape
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime
Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n
Bag of Tricks for Natural Policy Gradient Reinforcement Learning
Bag of Tricks for Natural Policy Gradient Reinforcement Learning [ArXiv] Setup Python 3.8.0 pip install -r req.txt Mujoco 200 license Main Files main.
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of
PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning
PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig
Out of Distribution Detection on Natural Adversarial Examples
OOD-on-NAE Research project on out of distribution detection for the Computer Vision course by Prof. Rob Fergus (CSCI-GA 2271) Paper out on arXiv - ht
Learning to Predict Gradients for Semi-Supervised Continual Learning
Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le
Code for project: "Learning to Minimize Remainder in Supervised Learning".
Learning to Minimize Remainder in Supervised Learning Code for project: "Learning to Minimize Remainder in Supervised Learning". Requirements and Envi
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN
Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an
CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces
CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces This is a repository for the following pape
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im
PaRT: Parallel Learning for Robust and Transparent AI
PaRT: Parallel Learning for Robust and Transparent AI This repository contains the code for PaRT, an algorithm for training a base network on multiple
Adaptable tools to make reinforcement learning and evolutionary computation algorithms.
Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto
In the AI for TSP competition we try to solve optimization problems using machine learning.
AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted
Implementation for "Conditional entropy minimization principle for learning domain invariant representation features"
Implementation for "Conditional entropy minimization principle for learning domain invariant representation features". The code is reproduced from thi
Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer.
DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to
Explanatory Learning: Beyond Empiricism in Neural Networks
Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch]
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec
PyTorch implementation of our paper How robust are discriminatively trained zero-shot learning models?
How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis
Check out the StyleGAN repo and place it in the same directory hierarchy as the present repo
Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W
CSPML (crystal structure prediction with machine learning-based element substitution)
CSPML (crystal structure prediction with machine learning-based element substitution) CSPML is a unique methodology for the crystal structure predicti
Model Agnostic Interpretability for Multiple Instance Learning
MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa
Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Novel and high-performance medical ima
Pytorch code for our paper Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains)
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.
shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t
Labelme is a graphical image annotation tool, It is written in Python and uses Qt for its graphical interface
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
A classification model capable of accurately predicting the price of secondhand cars
The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!
A beginnerβs guide to train and deploy machine learning pipelines in Python using PyCaret
This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).
Predict the spans of toxic posts that were responsible for the toxic label of the posts
toxic-spans-detection An attempt at the SemEval 2021 Task 5: Toxic Spans Detection. The Toxic Spans Detection task of SemEval2021 required participant
Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning
Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:
Melanoma Skin Cancer Detection using Convolutional Neural Networks and Transfer Learningπ΅π»ββοΈ
This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et
This library provides an abstraction to perform Model Versioning using Weight & Biases.
Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch
Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin
PyTorch implementation of the ideas presented in the paper Interaction Grounded Learning (IGL)
Interaction Grounded Learning This repository contains a simple PyTorch implementation of the ideas presented in the paper Interaction Grounded Learni
Voice Gender Recognition
In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.
Rax is a Learning-to-Rank library written in JAX
π¦ Rax: Composable Learning to Rank using JAX Rax is a Learning-to-Rank library written in JAX. Rax provides off-the-shelf implementations of ranking
This repository contains pre-trained models and some evaluation code for our paper Towards Unsupervised Dense Information Retrieval with Contrastive Learning
Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning This repository contains pre-trained models and some evaluation
Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis
TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described in
Bootstrapped Representation Learning on Graphs
Bootstrapped Representation Learning on Graphs This is the PyTorch implementation of BGRL Bootstrapped Representation Learning on Graphs The main scri
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction
Unsupervised Feature Loss (UFLoss) for High Fidelity Deep learning (DL)-based reconstruction Official github repository for the paper High Fidelity De
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation
AirPose AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation Check the teaser video This repository contains the code of A
Neural Tangent Generalization Attacks (NTGA)
Neural Tangent Generalization Attacks (NTGA) ICML 2021 Video | Paper | Quickstart | Results | Unlearnable Datasets | Competitions | Citation Overview
On Out-of-distribution Detection with Energy-based Models
On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr
Noether Networks: meta-learning useful conserved quantities
Noether Networks: meta-learning useful conserved quantities This repository contains the code necessary to reproduce experiments from "Noether Network
PyTorch META-DATASET (Few-shot classification benchmark)
PyTorch META-DATASET (Few-shot classification benchmark) This repo contains a PyTorch implementation of meta-dataset and a unified implementation of s
On the Adversarial Robustness of Visual Transformer
On the Adversarial Robustness of Visual Transformer Code for our paper "On the Adversarial Robustness of Visual Transformers"
Learning Time-Critical Responses for Interactive Character Control
Learning Time-Critical Responses for Interactive Character Control Abstract This code implements the paper Learning Time-Critical Responses for Intera
Adversarial vulnerability of powerful near out-of-distribution detection
Adversarial vulnerability of powerful near out-of-distribution detection by Stanislav Fort In this repository we're collecting replications for the ke
Spectral normalization (SN) is a widely-used technique for improving the stability and sample quality of Generative Adversarial Networks (GANs)
Why Spectral Normalization Stabilizes GANs: Analysis and Improvements [paper (NeurIPS 2021)] [paper (arXiv)] [code] Authors: Zinan Lin, Vyas Sekar, Gi
"Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion"(WWW 2021)
STAR_KGC This repo contains the source code of the paper accepted by WWW'2021. "Structure-Augmented Text Representation Learning for Efficient Knowled
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB)
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t
Compute execution plan: A DAG representation of work that you want to get done. Individual nodes of the DAG could be simple python or shell tasks or complex deeply nested parallel branches or embedded DAGs themselves.
Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In
Equivariant Imaging: Learning Beyond the Range Space
[Project] Equivariant Imaging: Learning Beyond the Range Space Project about the
Rl-quickstart - Reinforcement Learning Quickstart
Reinforcement Learning Quickstart To get setup with the repository, git clone ht
Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning
Neural Network Just a basic Neural Network module Usage Example Importing Module
DCSL - Generalizable Crowd Counting via Diverse Context Style Learning
DCSL Generalizable Crowd Counting via Diverse Context Style Learning Requirement
Self-supervised learning (SSL) is a method of machine learning
Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.
This is a Deep Leaning API for classifying emotions from human face and human audios.
Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee
FocusFace: Multi-task Contrastive Learning for Masked Face Recognition
FocusFace This is the official repository of "FocusFace: Multi-task Contrastive Learning for Masked Face Recognition" accepted at IEEE International C
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers
Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f
DTCN IJCAI - Sequential prediction learning framework and algorithm
DTCN This is the implementation of our paper "Sequential Prediction of Social Me
Reinforcement-learning - Repository of the class assignment questions for the course on reinforcement learning
DSE 314/614: Reinforcement Learning This repository containing reinforcement lea
Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications
Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s
CVAT is free, online, interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning
CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning This repository contains the code and relevant instructions
BERTopic is a topic modeling technique that leverages π€ transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions
BERTopic BERTopic is a topic modeling technique that leverages π€ transformers and c-TF-IDF to create dense clusters allowing for easily interpretable
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage
Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo
Simple and understandable swin-transformer OCR project
swin-transformer-ocr ocr with swin-transformer Overview Simple and understandable swin-transformer OCR project. The model in this repository heavily r
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms
A library for benchmarking, developing and deploying deep learning anomaly detection algorithms Key Features β’ Getting Started β’ Docs β’ License Introd
This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers
Official TensorFlow implementation of the unsupervised reconstruction model using zero-Shot Learned Adversarial TransformERs (SLATER). (https://arxiv.
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification [NeurIPS 2021] Abstract Multiple instance learn
List of awesome things around semantic segmentation π
Awesome Semantic Segmentation List of awesome things around semantic segmentation π Semantic segmentation is a computer vision task in which we label
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy
A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost
A boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast
Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the Machine Learning 4 Health Workshop
Detection-aided liver lesion segmentation Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the
This is a curated list of medical data for machine learning
Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl
This repository contains code, network definitions and pre-trained models for working on remote sensing images using deep learning
Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi
Generic ecosystem for feature extraction from aerial and satellite imagery
Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l
π°οΈ Awesome Satellite Imagery Datasets
Awesome Satellite Imagery Datasets List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datase