Supplementary code for the paper "Harnessing the flexibility of neural networks to predict dynamic theoretical parameters underlying human choice behavior" by Ger, Y., Nachmani, E., Wolf, L., & Sha…

Bayesian Parameter Estimation (based on pystan) of reinforcement learning and sequential sampling models, and combinations of the two.

Contains the code for reproducing the experiments and results of the paper "Neural Superstatistics: A Bayesian Method for Estimating Dynamic Models of Cognition".

A framework for combining artificial neural network with evidence accumulation models for lexical decision task

Repository for the Spring 2024 Cognitive Modeling Course at Rensselaer Polytechnic Institute (RPI).

A awesome list of (large-scale) public datasets on the Internet. (On-going collection)

A curated list of awesome Deep Learning tutorials, projects and communities.

A new markup-based typesetting system that is powerful and easy to learn.

course website for "evidence-based decision making"

Neural drift-diffusion model (NDDM) is a repository to integrate simultaneously both single-trial EEG measures and behavioral performance (response time and accuracy) to understand cognition.

A collection of (mostly) technical things every software developer should know about

Contains the code and data for reproducing the results of the paper "Validation and Comparison of Non-Stationary Cognitive Models: A Diffusion Model Application".

Code accompanying the paper "A Deep Learning Method for Comparing Bayesian Hierarchical Models".

A Python library for amortized Bayesian workflows using generative neural networks.

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Deprecated; up-to-date repository at https://github.com/bayesflow-org/Hierarchical-Model-Comparison

A Python implementation of active inference for Markov Decision Processes

Supplementary scripts for Step-by-step active inference modelling tutorial

Probabilistic programming via source rewriting

Active inference implementation of dynamic multi-armed bandits

Code for Observe or Bet project (Gershman Lab, 2016)

Data, analyses, and visualizations for paper: https://elifesciences.org/articles/65540#content

A collection of different Drift Diffusion Models implemented in the probabilistic programming language Stan.

Hierarchical Bayesian modeling of RLDM tasks, using R & Python

Seems like, there isn’t enough Bayesian power analysis talk out there. Let’s change that.