5360 Repositories
Python qiskit-machine-learning Libraries
Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification
next_best_view_rl Setup Clone the repository: git clone --recurse-submodules ... In 'third_party/zed-ros-wrapper': git checkout devel Install mujoco `
A cross-lingual COVID-19 fake news dataset
CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,
Codebase of deep learning models for inferring stability of mRNA molecules
Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen
Direct design of biquad filter cascades with deep learning by sampling random polynomials.
IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection, AAAI 2021.
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection This repository is an official implementation of the AAAI 2021 paper Co-mi
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.
mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do
A PyTorch implementation of paper "Learning Shared Semantic Space for Speech-to-Text Translation", ACL (Findings) 2021
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant
African language Speech Recognition - Speech-to-Text
Swahili-Speech-To-Text Table of Contents Swahili-Speech-To-Text Overview Scenario Approach Project Structure data: models: notebooks: scripts tests: l
A collection of learning outcomes data analysis using Python and SQL, from DQLab.
Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu
Additional tools for particle accelerator data analysis and machine information
PyLHC Tools This package is a collection of useful scripts and tools for the Optics Measurements and Corrections group (OMC) at CERN. Documentation Au
An end-to-end regression problem of predicting the price of properties in Bangalore.
Bangalore-House-Price-Prediction An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.
RL-driven agent playing tic-tac-toe on starknet against challengers.
tictactoe-on-starknet RL-driven agent playing tic-tac-toe on starknet against challengers. GUI reference: https://pythonguides.com/create-a-game-using
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.
The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering
[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt
Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification
Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification Suncheng Xiang Shanghai Jiao Tong University Over
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning This repository is the official implementation of CARE.
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).
DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
BuildingNet: Learning to Label 3D Buildings
BuildingNet This is the implementation of the BuildingNet architecture described in this paper: Paper: BuildingNet: Learning to Label 3D Buildings Arx
TCube generates rich and fluent narratives that describes the characteristics, trends, and anomalies of any time-series data (domain-agnostic) using the transfer learning capabilities of PLMs.
TCube: Domain-Agnostic Neural Time series Narration This repository contains the code for the paper: "TCube: Domain-Agnostic Neural Time series Narrat
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations This repo contains official code for the NeurIPS 2021 paper Imi
This repository is for EMNLP 2021 paper: It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data
InterpretationData This repository is for our EMNLP 2021 paper: It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpr
Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions
README Repository containing the code for the paper "Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions". Specifically, an
DP-CL(Continual Learning with Differential Privacy)
DP-CL(Continual Learning with Differential Privacy) This is the official implementation of the Continual Learning with Differential Privacy. If you us
Simple (but Strong) Baselines for POMDPs
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.
CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im
Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.
Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra
Deep Federated Learning for Autonomous Driving
FADNet: Deep Federated Learning for Autonomous Driving Abstract Autonomous driving is an active research topic in both academia and industry. However,
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D
The Official PyTorch Implementation of DiscoBox.
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib
Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"
DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei
PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"
PASS - Official PyTorch Implementation [CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning Fei Zhu, Xu-Yao Zhang, Chu
[ICCV 2021 Oral] Deep Evidential Action Recognition
DEAR (Deep Evidential Action Recognition) Project | Paper & Supp Wentao Bao, Qi Yu, Yu Kong International Conference on Computer Vision (ICCV Oral), 2
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
BasicRL: easy and fundamental codes for deep reinforcement learning。It is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up.
BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is
The Few-Shot Bot: Prompt-Based Learning for Dialogue Systems
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems This repository includes the dataset, experiments results, and code for the paper: Few-Shot B
Reinforcement Learning for the Blackjack
Reinforcement Learning for Blackjack Author: ZHA Mengyue Math Department of HKUST Problem Statement We study playing Blackjack by reinforcement learni
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation The code repository for "Audio-Visual Generalized Few-Shot Learning with
Jarvis Project is a basic virtual assistant that uses TensorFlow for learning.
Jarvis_proyect Jarvis Project is a basic virtual assistant that uses TensorFlow for learning. Latest version 0.1 Features: Good morning protocol Tell
This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.
This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.
Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021.
SphereRPN Code for the paper SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection, ICIP 2021. Authors: Th
FACIAL: Synthesizing Dynamic Talking Face With Implicit Attribute Learning. ICCV, 2021.
FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning PyTorch implementation for the paper: FACIAL: Synthesizing Dynamic Talking
Dual Adaptive Sampling for Machine Learning Interatomic potential.
DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong
The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
SubTab: Author: Talip Ucar ([email protected]) The official implementation of the paper, SubTab: Subsetting Features of Tabular Data for Self-Supervis
Official codebase for Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
Legged Robots that Keep on Learning Official codebase for Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World, whic
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021)
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021) This repository contains the official implemen
[ICCV21] Code for RetrievalFuse: Neural 3D Scene Reconstruction with a Database
RetrievalFuse Paper | Project Page | Video RetrievalFuse: Neural 3D Scene Reconstruction with a Database Yawar Siddiqui, Justus Thies, Fangchang Ma, Q
[ICCV 2021 Oral] SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
This repository contains the source code for the paper SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer (ICCV 2021 Oral). The project page is here.
Pytorch implementation for our ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering".
TRAnsformer Routing Networks (TRAR) This is an official implementation for ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visu
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
Permute Me Softly: Learning Soft Permutations for Graph Representations
Permute Me Softly: Learning Soft Permutations for Graph Representations
Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation
FLAME Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation, accepted at the 17th IEEE Internation Co
PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)
PyTorch implementation of DUL (Data Uncertainty Learning in Face Recognition, CVPR2020)
Framework to build and train RL algorithms
RayLink RayLink is a RL framework used to build and train RL algorithms. RayLink was used to build a RL framework, and tested in a large-scale multi-a
Uses WiFi signals :signal_strength: and machine learning to predict where you are
Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.
[ICCV '21] In this repository you find the code to our paper Keypoint Communities
Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,
Experiments for distributed optimization algorithms
Network-Distributed Algorithm Experiments -- This repository contains a set of optimization algorithms and objective functions, and all code needed to
Vision-and-Language Navigation in Continuous Environments using Habitat
Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations
Tribuo - A Java machine learning library
Tribuo - A Java prediction library (v4.1) Tribuo is a machine learning library in Java that provides multi-class classification, regression, clusterin
Awesome Weak-Shot Learning
Awesome Weak-Shot Learning In weak-shot learning, all categories are split into non-overlapped base categories and novel categories, in which base cat
A game theoretic approach to explain the output of any machine learning model.
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis
StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110
NVIDIA Deep Learning Examples for Tensor Cores
NVIDIA Deep Learning Examples for Tensor Cores Introduction This repository provides State-of-the-Art Deep Learning examples that are easy to train an
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
This project aims to segment 4 common retinal lesions from Fundus Images.
This project aims to segment 4 common retinal lesions from Fundus Images.
Official Pytorch implementation of Meta Internal Learning
Official Pytorch implementation of Meta Internal Learning
Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
GndNet: Fast Ground plane Estimation and Point Cloud Segmentation for Autonomous Vehicles. Authors: Anshul Paigwar, Ozgur Erkent, David Sierra Gonzale
Learning High-Speed Flight in the Wild
Learning High-Speed Flight in the Wild This repo contains the code associated to the paper Learning Agile Flight in the Wild. For more information, pl
Machine Learning Algorithms
Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with
Learning to Reach Goals via Iterated Supervised Learning
Vanilla GCSL This repository contains a vanilla implementation of "Learning to Reach Goals via Iterated Supervised Learning" proposed by Dibya Gosh et
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:
A Python script to capture images from multiple webcams at once and save them into your local machine
Capturing multiple images at once from Webcam Using OpenCV Capture multiple image by accessing the webcam of your system and save it to your machine.
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.
Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression
Neural network for recognizing the gender of people in photos
Neural Network For Gender Recognition How to test it? Install requirements.txt file using pip install -r requirements.txt command Run nn.py using pyth
Algorithmic and AI MIDI Drums Generator Implementation
Algorithmic and AI MIDI Drums Generator Implementation
Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)
Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)
A geometric deep learning pipeline for predicting protein interface contacts.
A geometric deep learning pipeline for predicting protein interface contacts.
🎓Automatically Update CV Papers Daily using Github Actions (Update at 12:00 UTC Every Day)
🎓Automatically Update CV Papers Daily using Github Actions (Update at 12:00 UTC Every Day)
Deep learning algorithms for muon momentum estimation in the CMS Trigger System
Deep learning algorithms for muon momentum estimation in the CMS Trigger System The Compact Muon Solenoid (CMS) is a general-purpose detector at the L
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"
StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110
A Robust Avatar Generator with a huge number of templates
CoolAvatars Welcome to this repository of CoolAvatars. Using this project, you can generate cool avatars not only from the samples present in my image
using Machine Learning Algorithm to classification AppleStore application
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
The Hitchiker's Guide to PyTorch
The Hitchiker's Guide to PyTorch
Graphsignal is a machine learning model monitoring platform.
Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model performance and availability.
This is a public repo where code samples are stored for the book Practical MLOps.
[Book-2021] Practical MLOps O'Reilly Book
XManager: A framework for managing machine learning experiments 🧑🔬
XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction with experiments is done via XManager's APIs through Python launch scripts.
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).