7047 Repositories
Python learning-with-limited-labeled-data Libraries
Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".
DeepOrder Implementation of DeepOrder for the paper "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing". Project
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations
Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"
StyleAttack Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer" Prepare Pois
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.
Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte
A torch.Tensor-like DataFrame library supporting multiple execution runtimes and Arrow as a common memory format
TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou
Collection of Docker images for ML/DL and video processing projects
Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real Time Video Interpolation arXiv | YouTube | Colab | Tutorial | Demo Table of Contents Introduction Collection Usage Evaluation Training and
Youtube Downloader is a Graphic User Interface(GUI) that lets users download a Youtube Video or Audio through a URL
Youtube Downloader This Python and Tkinter based GUI allows users to directly download the Best Resolution Videos and Audios from Youtube. Pa-fy Insta
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch
revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f
Bittensor - an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence
At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.
DataPrep — The easiest way to prepare data in Python
DataPrep — The easiest way to prepare data in Python
Solutions of Reinforcement Learning 2nd Edition
Solutions of Reinforcement Learning, An Introduction
LibreLingo🐢 🌎 📚 a community-owned language-learning platform
LibreLingo's mission is to create a modern language-learning platform that is owned by the community of its users. All software is licensed under AGPLv3, which guarantees the freedom to run, study, share, and modify the software. Course authors are encouraged to release their courses with free licenses.
A data visualization curriculum of interactive notebooks.
A data visualization curriculum of interactive notebooks, using Vega-Lite and Altair. This repository contains a series of Python-based Jupyter notebooks.
A JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short.
BraVe This is a JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short. The model provided in this package wa
Python Library for Signal/Image Data Analysis with Transport Methods
PyTransKit Python Transport Based Signal Processing Toolkit Website and documentation: https://pytranskit.readthedocs.io/ Installation The library cou
BLEURT is a metric for Natural Language Generation based on transfer learning.
BLEURT: a Transfer Learning-Based Metric for Natural Language Generation BLEURT is an evaluation metric for Natural Language Generation. It takes a pa
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a
Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.
DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Preprocess file of the dataset used in implicit sub-populations: (Demographic groups
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
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)
LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning
DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts
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,
Ground truth data for the Optical Character Recognition of Historical Classical Commentaries.
OCR Ground Truth for Historical Commentaries The dataset OCR ground truth for historical commentaries (GT4HistComment) was created from the public dom
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
The source code for 'Noisy-Labeled NER with Confidence Estimation' accepted by NAACL 2021
Kun Liu*, Yao Fu*, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, Sheng Gao. Noisy-Labeled NER with Confidence Estimation. NAACL 2021. [arxiv]
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
Scrape data on SpaceX: Capsules, Rockets, Cores, Roadsters, SpaceX Info
SpaceX Sofware I developed software to scrape data on SpaceX: Capsules, Rockets, Cores, Roadsters, SpaceX Info to use the software you need Python a
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
Code & Data for the Paper "Time Masking for Temporal Language Models", WSDM 2022
Time Masking for Temporal Language Models This repository provides a reference implementation of the paper: Time Masking for Temporal Language Models
A Python package that scrapes Google News article data while remaining undetected by Google.
A Python package that scrapes Google News article data while remaining undetected by Google. Our scraper can scrape page data up until the last page and never trigger a CAPTCHA (download stats: https://pepy.tech/project/GoogleNewsScraper)
Using Selenium with Python to Web Scrap Popular Youtube Tech Channels.
Web Scrapping Popular Youtube Tech Channels with Selenium Data Mining, Data Wrangling, and Exploratory Data Analysis About the Data Web scrapi
👁️ Tool for Data Extraction and Web Requests.
httpmapper 👁️ Project • Technologies • Installation • How it works • License Project 🚧 For educational purposes. This is a project that I developed,
The open-source web scrapers that feed the Los Angeles Times California coronavirus tracker.
The open-source web scrapers that feed the Los Angeles Times' California coronavirus tracker. Processed data ready for analysis is available at datade
A tool for scraping and organizing data from NewsBank API searches
nbscraper Overview This simple tool automates the process of copying, pasting, and organizing data from NewsBank API searches. Curerntly, nbscrape onl
A web scraping pipeline project that retrieves TV and movie data from two sources, then transforms and stores data in a MySQL database.
New to Streaming Scraper An in-progress web scraping project built with Python, R, and SQL. The scraped data are movie and TV show information. The go
A tool to easily scrape youtube data using the Google API
YouTube data scraper To easily scrape any data from the youtube homepage, a youtube channel/user, search results, playlists, and a single video itself
Universal Reddit Scraper - A comprehensive Reddit scraping command-line tool written in Python.
Universal Reddit Scraper - A comprehensive Reddit scraping command-line tool written in Python.
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
Recommendations from Cramer: On the show Mad-Money (CNBC) Jim Cramer picks stocks which he recommends to buy. We will use this data to build a portfolio
Backtesting the "Cramer Effect" & Recommendations from Cramer Recommendations from Cramer: On the show Mad-Money (CNBC) Jim Cramer picks stocks which
DaDRA (day-druh) is a Python library for Data-Driven Reachability Analysis.
DaDRA (day-druh) is a Python library for Data-Driven Reachability Analysis. The main goal of the package is to accelerate the process of computing estimates of forward reachable sets for nonlinear dynamical systems.
Statistical Analysis 📈 focused on statistical analysis and exploration used on various data sets for personal and professional projects.
Statistical Analysis 📈 This repository focuses on statistical analysis and the exploration used on various data sets for personal and professional pr
pyETT: Python library for Eleven VR Table Tennis data
pyETT: Python library for Eleven VR Table Tennis data Documentation Documentation for pyETT is located at https://pyett.readthedocs.io/. Installation
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
Python Package for DataHerb: create, search, and load datasets.
The Python Package for DataHerb A DataHerb Core Service to Create and Load Datasets.
A powerful data analysis package based on mathematical step functions. Strongly aligned with pandas.
The leading use-case for the staircase package is for the creation and analysis of step functions. Pretty exciting huh. But don't hit the close button
HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets
HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets that can be described as multidimensional arrays o
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
GWpy is a collaboration-driven Python package providing tools for studying data from ground-based gravitational-wave detectors
GWpy is a collaboration-driven Python package providing tools for studying data from ground-based gravitational-wave detectors. GWpy provides a user-f
Open Data Cube analyses continental scale Earth Observation data through time
Open Data Cube Core Overview The Open Data Cube Core provides an integrated gridded data analysis environment for decades of analysis ready earth obse
Toolchest provides APIs for scientific and bioinformatic data analysis.
Toolchest Python Client Toolchest provides APIs for scientific and bioinformatic data analysis. It allows you to abstract away the costliness of runni
A data analysis using python and pandas to showcase trends in school performance.
A data analysis using python and pandas to showcase trends in school performance. A data analysis to showcase trends in school performance using Panda
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.
Repositori untuk menyimpan material Long Course STMKGxHMGI tentang Geophysical Python for Seismic Data Analysis
Long Course "Geophysical Python for Seismic Data Analysis" Instruktur: Dr.rer.nat. Wiwit Suryanto, M.Si Dipersiapkan oleh: Anang Sahroni Waktu: Sesi 1
The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.
The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.
Universal data analysis tools for atmospheric sciences
U_analysis Universal data analysis tools for atmospheric sciences Script written in python 3. This file defines multiple functions that can be used fo
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
Django3 web app that renders OpenWeather API data ☁️☁️
nz-weather For a live build, visit - https://brandonru.pythonanywhere.com/ NZ Openweather API data rendered using Django3 and requests ☀️ Local Run In
Trained on Simulated Data, Tested in the Real World
Trained on Simulated Data, Tested in the Real World
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
Helper tools to construct probability distributions built from expert elicited data for use in monte carlo simulations.
Elicited Helper tools to construct probability distributions built from expert elicited data for use in monte carlo simulations. Credit to Brett Hoove
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
A synthetic texture-invariant dataset for object detection of UAVs
A synthetic dataset for object detection of UAVs This repository contains a synthetic datasets accompanying the paper Sim2Air - Synthetic aerial datas
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
Perform Linear Classification with Multi-way Data
MultiwayClassification This is an R package to perform linear classification for data with multi-way structure. The distance-weighted discrimination (
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
This repository contains all data used for writing a research paper Multiple Object Trackers in OpenCV: A Benchmark, presented in ISIE 2021 conference in Kyoto, Japan.
OpenCV-Multiple-Object-Tracking Python is version 3.6.7 to install opencv: pip uninstall opecv-python pip uninstall opencv-contrib-python pip install
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