jsPsych — Peer-reviewed • Rank 22.7 • Science 100%

jsPsych: Enabling an Open-Source Collaborative Ecosystem of Behavioral Experiments - Published in JOSS (2023)

PyExperimenter — Peer-reviewed • Rank 12.5 • Science 100%

PyExperimenter: Easily distribute experiments and track results - Published in JOSS (2023)

PurpleCaffeine — Peer-reviewed • Rank 7.4 • Science 100%

PurpleCaffeine: tracking of quantum programs and experiments - Published in JOSS (2023)

Neuropsydia.py — Peer-reviewed • Rank 8.6 • Science 95%

Neuropsydia.py: A Python Module for Creating Experiments, Tasks and Questionnaires - Published in JOSS (2017)

JOAN — Peer-reviewed • Rank 6.2 • Science 95%

JOAN: a framework for human-automated vehicle interaction experiments in a virtual reality driving simulator - Published in JOSS (2023)

MyPTV — Peer-reviewed • Rank 5.3 • Science 93%

MyPTV: A Python Package for 3D Particle Tracking - Published in JOSS (2022)

The Experiment Factory — Peer-reviewed • Rank 13.0 • Science 77%

The Experiment Factory: Reproducible Experiment Containers - Published in JOSS (2018)

https://github.com/silx-kit/silx • Rank 21.2 • Science 59%

silx toolkit

wifi-based-landmark-estimation • Rank 1.4 • Science 67%

Research project files concerning non-stationary landmark localization

mep • Rank 2.2 • Science 54%

Project MEP: Meme Evolution programme. A terraformed multi-language library to do statistical experiments in Twitter.

ebtorch • Rank 10.0 • Science 44%

🤓🔥 Collection of PyTorch additions, extensions, utilities, uses and abuses

https://github.com/jspsych/jspsych-contrib • Rank 16.4 • Science 36%

An open repository of jsPsych plugins and extensions, without any official support

qrlabelr • Rank 8.7 • Science 36%

An open-source software for designing print-ready plot labels affixed with QR codes

autolab • Rank 11.4 • Science 23%

Python package for laboratory instruments control and scientific experiments automation

mlsurvlrnrs • Rank 7.7 • Science 26%

Survival learners for the `mlexperiments` R 📦

https://github.com/arogozhnikov/infiniteboost • Rank 6.8 • Science 20%

InfiniteBoost: building infinite ensembles with gradient descent

https://github.com/plynx-team/plynx • Rank 12.0 • Science 13%

PLynx is a domain agnostic platform for managing reproducible experiments and data-oriented workflows.

built • Rank 6.6 • Science 13%

BuilT - Build a Trainer of deep neural networks

dropR • Science 26%

drop out analysis with R and shiny

https://github.com/fgcz/bfabricshiny • Science 49%

Manage life sciences data using R and b-fabric - a WSDL/REST interface and a tool box; main focus on MS data

autosubmit • Science 67%

org.cicirello • Science 57%

Experiments with simulated annealing and an optimized version of the modified lam adaptive annealing schedule

https://github.com/lazyscribe/lazyscribe • Science 26%

Lightweight, lazy model experiment logging

demos • Science 44%

demonstrations of engineering principles with experimental data and models; demostraciones de principios de ingeniería con datos experimentales y modelos

https://github.com/memory-formation/psychos • Science 26%

Create simple experiments in Python

continual-learning-baselines • Science 67%

Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.