For running psychology and neuroscience experiments
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Updated
May 10, 2024 - Python
For running psychology and neuroscience experiments
YACS -- Yet Another Configuration System
Create behavioral experiments in a browser using JavaScript
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
A JavaScript port of Facebook's PlanOut Experimentation Framework
Bayesian Optimization and Design of Experiments
Experimental design and (multi-objective) bayesian optimization.
Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
Olympus: a benchmarking framework for noisy optimization and experiment planning
This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.
Experimental design and Bayesian optimization library in Python/PyTorch
Active Bayesian Causal Inference (Neurips'22)
An R Package and Shiny App for generating matched stimuli for factiorial-design experiments.
ParamHelpers Next Generation
Repository collecting resources and best practices to improve experimental rigour in deep learning research.
Lightweight tools for experimental design and multi-objective optimization.
Design of Experiments in Julia
A minimalist framework for rapid server side applications prototyping in C++ with dependency injection support.
Causal Inference Using Quasi-Experimental Methods
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