Python Positive-unlabeled-learning Resources

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec

EDSR modelling A Github repository for deep-learning image enhancement, pore-network and continuum modelling from X-Ray Micro-CT images. The repositor

Deep Learning Algorithms for Hedging with Frictions This repository contains the Forward-Backward Stochastic Differential Equation (FBSDE) solver and

Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy

Fair-SSL Source Code for ICSE 2022 Paper - Can We Achieve Fairness Using Semi-Supervised Learning? Ethical bias in machine learning models has become

An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea

GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context

README The code is based on the ILswiss. To run the code, use python run_experiment.py --nosrun -e your YAML file -g gpu id Generally, run_experim

causal-bald | Abstract | Installation | Example | Citation | Reproducing Results DUE An implementation of the methods presented in Causal-BALD: Deep B

Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require

ML-PersRef This repository has python code (in jupyter notebooks) for both of the following papers: ML-PersRef: A Machine Learning-based Personalized

JAXGA - JAX Geometric Algebra GitHub | Docs JAXGA is a Geometric Algebra package on top of JAX. It can handle high dimensional algebras by storing onl

DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model

Unsupervised Learning of Compositional Energy Concepts This is the pytorch code for the paper Unsupervised Learning of Compositional Energy Concepts.

DRLVIS - Visualising Deep Reinforcement Learning Created by Marios Sirtmatsis with the support of Alex Bäuerle. DRLVis is an application used for visu

AutoDL AutoDL automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few line

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

A python library for highly configurable transformers - easing model architecture search and experimentation.

PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin

Robot Action Primitives (RAPS) This repository is the official implementation of Accelerating Robotic Reinforcement Learning via Parameterized Action

Repository for Open Source Reinforcement Learning Framework JORLDY

ActiveLearningDemo How to run step one put the dataset folder and use command below to split the dataset to the required structure run utils.py For ea

Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation [Project website] [Paper] This project is a PyTorch i

AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just

prompt2slip This library is testing the ethics of language models by using natural adversarial texts. This tool allows for short and simple code and v

Who's there? The spiritual successor to knockknock for PyTorch Lightning, to get a notification when your training is complete or when it crashes duri

Open Source Photos Platform Powered by PyTorch. Submission for PyTorch Annual Hackathon 2021.

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

duality Data science, Data manipulation and Machine learning package. Use permitted according to the terms of use and conditions set by the attached l

ATS About Source code of the paper Meta-learning with an Adaptive Task Scheduler. If you find this repository useful in your research, please cite the

Fast Reinforcement Learning This is a repo where I implement the algorithms in the paper, Fast reinforcement learning with generalized policy updates.

SDK: Overview of the Kubeflow pipelines service Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on

Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac

DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning

PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

Get Fooled for the Right Reason Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness throu

DSEE Codes for [Preprint] DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Ch

OpenBox Doc | OpenBox中文文档 OpenBox: Generalized and Efficient Blackbox Optimization System OpenBox is an efficient and generalized blackbox optimizatio

Revealing and Protecting Labels in Distributed Training

FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.

FIW Data Development Kit Table of Contents Introduction Families In the Wild Database Publications Organization To Do License Getting Involved Introdu

Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in

gtfs2vec This is a companion repository for a gtfs2vec - Learning GTFS Embeddings for comparing PublicTransport Offer in Microregions publication. Vis

Evaluating deep transfer learning for whole-brain cognitive decoding This README file contains the following sections: Project description Repository

Amortized Assimilation This repository contains a PyTorch implementation of the paper Learning to Assimilate in Chaotic Dynamical Systems. Abstract: T

SusPedal-Gen This is the official repository of Learning to Generate Piano Music With Sustain Pedals Demo Page Dataset The dataset used in this projec

Corruption Invariant Learning for Re-identification The official repository for Benchmarks for Corruption Invariant Person Re-identification (NeurIPS

RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed

Federated Learning DAG Experiments This repository contains software artifacts to reproduce the experiments presented in the Middleware '21 paper "Imp

Mixture Proportion Estimation and PU Learning: A Modern Approach This repository is the official implementation of Mixture Proportion Estimation and P

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri

PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

Transfer learning approach to bicycle sharing systems station location planning using OpenStreetMap Companion repository to the paper accepted at the

FedFly: Towards Migration in Edge-based Distributed Federated Learning About the research Due to mobility, a device participating in Federated Learnin

Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation Introduction 📋 Official implementation of Explainable Robust Learnin

META-RS This is the companion code for the paper "Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks" by Yatsu

Realistic galaxy simulation via score-based generative models Official code for 'Realistic galaxy simulation via score-based generative models'. We us

mpl-image-labeller Use Matplotlib to label images for classification. Works anywhere Matplotlib does - from the notebook to a standalone gui! For more

Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le

Deep-Learning-based-Spectrum-Sensing Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectru

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

The Simpsons and Machine Learning: What makes an Episode Great? Check out my Medium article on this! PROBLEM: The Simpsons has had a decline in qualit

PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:

UPFlow: Upsampling Pyramid for Unsupervised Optical Flow Learning By Kunming Luo, Chuan Wang, Shuaicheng Liu, Haoqiang Fan, Jue Wang, Jian Sun Megvii

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap

A large-scale database for graph representation learning

The purpose of this repo is to make it easy to get started with JAX. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning JAX.

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

fMRIprep Pipeline To Machine Learning(Demo) 所有配置均在config.py文件下定义 前置环境(lilab) 各个节点均安装docker，并有fmripre的镜像 可以使用conda中的base环境（相应的第三份包之后更新） 1. fmriprep scr

DataStructure Journey This repo represents all we learned and are learning in Data Structure course which is based on CLRS book and is being taught by

dbv Decision Border Visualizer for Classification Algorithms Project description A python package for Machine Learning Engineers who want to visualize

Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

A Comprehensive Study on Learning-Based PE Malware Family Classification Methods Datasets Because of copyright issues, both the MalwareBazaar dataset

Gradient CLI Get started: Create Account • Install CLI • Tutorials • Docs Resources: Website • Blog • Support • Contact Sales Gradient is an an end-to

OnsagerNet Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks This is the original pyTorch implemenati

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo

Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested

waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che

HFGI: High-Fidelity GAN Inversion for Image Attribute Editing High-Fidelity GAN Inversion for Image Attribute Editing Update: We released the inferenc

Lossy Compression for Lossless Prediction Using: Training: This repostiory contains our implementation of the paper: Lossy Compression for Lossless Pr

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin

Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric

Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes

Ralph is a command-line tool to fetch, extract, convert and push your tracking logs (aka learning events) from various storage backends to your

Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear

Anderson Accelerated Deep Learning (AADL) AADL is a Python package that implements the Anderson acceleration to speed-up the training of deep learning

Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide

SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Au

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro