Pinned Repositories
catlearn
Formal Psychological Models of Categorization and Learning
COCOdev_cross
COCO model code used in Yim et al. (2020) Sources of Interference in Memory across Development
compcogsci-3016
Danielle Navarro & Andrew Perfors' class on "Computational Cognitive Science"
ComputationalCognitiveModeling
This source is for "ComputationalCognitiveModeling" class in Hanyang university. (2023-2)
ET-remove-artifacts
Tool that allows users to clean pupil data
example-models
Example models for Stan
functions-experiments
functions-matlab
Common functions employed throughout various Ultralytics projects.
PsychtoolboxWorkshop
tutorial-git
:blue_book: 어떻게 깃을 사용하는지 빠르게 알아봅시다. (Quick learn How to use Git.)
lapensee's Repositories
lapensee/PsychtoolboxWorkshop
lapensee/tutorial-git
:blue_book: 어떻게 깃을 사용하는지 빠르게 알아봅시다. (Quick learn How to use Git.)
lapensee/catlearn
Formal Psychological Models of Categorization and Learning
lapensee/COCOdev_cross
COCO model code used in Yim et al. (2020) Sources of Interference in Memory across Development
lapensee/compcogsci-3016
Danielle Navarro & Andrew Perfors' class on "Computational Cognitive Science"
lapensee/ComputationalCognitiveModeling
This source is for "ComputationalCognitiveModeling" class in Hanyang university. (2023-2)
lapensee/ET-remove-artifacts
Tool that allows users to clean pupil data
lapensee/example-models
Example models for Stan
lapensee/functions-experiments
lapensee/functions-matlab
Common functions employed throughout various Ultralytics projects.
lapensee/Mat-HDIcal
Calculating highest density interval (HDI) in matlab. A total copycat from John Kruschke's code.
lapensee/MCMC_tutorial
MCMC algorithms
lapensee/PsychopyExamples
lapensee/PsychoPyParadigms
Experimental Paradigms written for PsychoPy
lapensee/rminr
Research Methods in R
lapensee/WAX
The respository describing a novel datasets for word association explanations
lapensee/working_memory_tests
Working memory tests on JavaScript (digit span, operation span, visual array, spatial span)
lapensee/WS19_Python_for_Psychologists