Cognitive Models: Computational Modeling of Cognitive Processes with Bayesian Mixed Models in Julia
-
Updated
Aug 1, 2024 - Jupyter Notebook
Cognitive Models: Computational Modeling of Cognitive Processes with Bayesian Mixed Models in Julia
Documentation, Instructions and other helpful information regarding working with the "Data Donation Module" (DDM-UZH)
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.
Boundary Element Method in 2D based on Crouch & Starfield book
Successor of Poly3D and iBem3D
Website with data and code for our manuscript on respiratory brain coupling in perception.
The Tornado 🌪️ framework, designed and implemented for adaptive online learning and data stream mining in Python.
Python GUI for the quick processing, analysis and plotting of differential dynamic microscopy data
PyBEAM: A Bayesian approach to parameter inference for a wide class of binary evidence accumulation models
This .Net/.Net Core class library is used to interface with existing IBM i database, program calls, CL commands, service programs and data queues via the PASE based xmlservice-cli PASE command program or regular qsh/bash commands. qsh/bash commands can be used to interface with any qsh/pase based utilities such as the IBM i db2util utility
A Displacement Discontinuity Method (DDM) implementation for fault slip
Converts GPS coordinates from DD to DDM format
Add a description, image, and links to the ddm topic page so that developers can more easily learn about it.
To associate your repository with the ddm topic, visit your repo's landing page and select "manage topics."