Python Scalable-marl Resources

DendroMap DendroMap is an interactive tool to explore large-scale image datasets used for machine learning. A deep understanding of your data can be v

PyDeepFakeDet An integrated and scalable library for Deepfake detection research. Introduction PyDeepFakeDet is an integrated and scalable Deepfake de

SOFIMA SOFIMA (Scalable Optical Flow-based Image Montaging and Alignment) is a tool for stitching, aligning and warping large 2d, 3d and 4d microscopy

CAKE ACL 2022: CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion Introduction This is the PyTorch implementation

Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo

BiDR Repo for WWW 2022 paper: Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. Requirements torch==

EvoJAX: Hardware-Accelerated Neuroevolution EvoJAX is a scalable, general purpose, hardware-accelerated neuroevolution toolkit. Built on top of the JA

Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec

INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas

MarlBot A private bot for controlling monkeys and turtles. Why does this bot exist? The bot exists as a general-purpose community bot for a select few

Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy

Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @

Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to

Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin

ClusterFuzz ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database. Its original intention is to monitor cryptocurrency related channels, but it can be configured to read any Telegram data that is accessible through the API.

Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

SimpleQ A simple, infinitely scalable, SQS based queue. Meta Author: Randall Degges Email: [email protected] Site: http://www.rdegges.com Status: in-devel

PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont

Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN Official code for NeurIPS 2021 paper "Towards Scalable Unpaired Virtu

The source code is temporariy removed, as we are solving potential copyright and license issues with GRANSO (http://www.timmitchell.com/software/GRANS

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

Introduction This is the source code of our TCSVT 2021 paper "MARS: Learning Modality-Agnostic Representation for Scalable Cross-media Retrieval". Ple

NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle

mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/

This Python library was evolved at IronPort Systems and has been provided as open source by Cisco Systems under an MIT license. Intro Shrapnel is a li

Gosling.js Gosling.js is a declarative grammar for interactive (epi)genomics visualization on the Web. ⚠️ Please be aware that the grammar of Gosling.

This folder contains the code for 'Scalable Variational Approaches for Bayesian Causal Discovery'. Installation To install, use conda with conda env c

mlforecast Scalable machine learning based time series forecasting. Install PyPI pip install mlforecast Optional dependencies If you want more functio

🌟 HNSW + PostgreSQL Indexer HNSWPostgreSQLIndexer Jina is a production-ready, scalable Indexer for the Jina neural search framework. It combines the

Scalable Multi-Agent Reinforcement Learning 1. Featured algorithms: Value Function Factorization with Variable Agent Sub-Teams (VAST) [1] 2. Implement

G-PATE This is the official code base for our NeurIPS 2021 paper: "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of T

ML-Decoder: Scalable and Versatile Classification Head Paper Official PyTorch Implementation Tal Ridnik, Gilad Sharir, Avi Ben-Cohen, Emanuel Ben-Baru

advantage-weighted-regression Implementation of Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning, by Peng et al. (

NCVX NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. Please check https://ncvx.org for detailed instruction

Few-shot Deep HDR Deghosting This repository contains code and pretrained models for our paper: Self-Gated Memory Recurrent Network for Efficient Scal

ML-Decoder: Scalable and Versatile Classification Head Paper Official PyTorch Implementation Tal Ridnik, Gilad Sharir, Avi Ben-Cohen, Emanuel Ben-Baru

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

MEMORABLE This repository contains the source code accompanying our ICCV 2021 paper. A Machine Teaching Framework for Scalable Recognition Pei Wang, N

Better Categories 4All: A multi-tenant multi-client product categorising stack The steps to reproduce training and inference are in the end of this fi

(pytorch) Gen-LaneNet: a generalized and scalable approach for 3D lane detection Introduction This is a pytorch implementation of Gen-LaneNet, which p

IROS21 information To test the code and reproduce the experiments, follow the installation steps in Installation.md. Afterwards, follow the steps in E

scalableMARL Scalable Reinforcement Learning Policies for Multi-Agent Control CD. Hsu, H. Jeong, GJ. Pappas, P. Chaudhari. "Scalable Reinforcement Lea

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

How to use this repository This repository contains code to replicate the results of "Universal inference meets random projections: a scalable test fo

An pytorch implementation of Masked Autoencoders Are Scalable Vision Learners This is a coarse version for MAE, only make the pretrain model, the fine

Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

EfficientDet This is an implementation of EfficientDet for object detection on Keras and Tensorflow. The project is based on the official implementati

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

A clean and extensible PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners A PyTorch re-implementation of Mask Autoencoder trai

Resilient projection-based consensus actor-critic (RPBCAC) algorithm We implement the RPBCAC algorithm with nonlinear approximation from [1] and focus

Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control Official implementation of: Cooperative multi-agent reinfor

Scalable Intervention Target Estimation in Linear Models Implementation of the paper Scalable Intervention Target Estimation in Linear Models (NeurIPS

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

StackNet This repository contains StackNet Meta modelling methodology (and software) which is part of my work as a PhD Student in the computer science

Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose

Ansible Amazon Base Repository Ansible Amazon Base Repository About Setting Up Ansible Environment Configuring Python VENV and Ansible Editor Configur

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners This repository is built upon BEiT, thanks very much! Now, we on

AutomaticUSnavigation Investigating automatic navigation towards standard US views integrating MARL with the virtual US environment developed in CT2US

Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu

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

Aquarius Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions NOTE: We are currently going through the open-source process requir

Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati

collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do

Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

JumpDetectR Name of QuantLet : JumpDetectR Published in : 'To be published as "Jump dynamics in high frequency crypto markets"' Description : 'Scala

scalable-gol-computer This is a computer built in Conway’s game of life. It supports variable sizes of 8, 16 and 32 bit. Maximum program size: 256 lin

PyTorch Project Template is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial PyTorch P

UpliftML is a Python package for scalable unconstrained and constrained uplift modeling from experimental data. To accommodate working with big data, the package uses PySpark and H2O models as base learners for the uplift models. Evaluation functions expect a PySpark dataframe as input.

WobblyStitcher Introduction A scalable implementation of WobblyStitcher Dependencies $ python -m pip install numpy scikit-image Visualization ImageJ

pytorch-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em

GIANT Code and data for paper "GIANT: Scalable Creation of a Web-scale Ontology" https://arxiv.org/pdf/2004.02118.pdf Please cite our paper if this pr

Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding PyTorch implementation for the Scalable Attentive Sentence-Pair Modeling vi

PyGAS: Auto-Scaling GNNs in PyG PyGAS is the practical realization of our G NN A uto S cale (GAS) framework, which scales arbitrary message-passing GN

To run the project, run: conda create --name env python=3.7 pip install -r requirements.txt python run.py To-do: Add direction to the state space Take

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

Intro This is the repository for CVPR2021 Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales Vehicle Sam

collie_recs Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Coll

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

Segcache: a memory-efficient and scalable in-memory key-value cache for small objects This repo contains the code of Segcache described in the followi

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

thunder scalable analysis of image and time series analysis in python Thunder is an ecosystem of tools for the analysis of image and time series data

MARL Tricks Our codes for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implemented and standardiz

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear