mqg's repositories
fitting-Ornstein-Uhlenbeck-model
template of using probability density approximation to fit ou model
NORA_WhitakerVendetti_DevSci2017
Code to reproduce the figures in the NORA manuscript "Neuroscientific insights into the development of analogical reasoning".
berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
ComplexSpan
A Psychopy implementation of a working memory span task
DeepLearning
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
DeepLearningPython
neuralnetworksanddeeplearning.com integrated scripts for Python 3.5.2 and Theano with CUDA support
DMpy
A package for fitting computational models of decision making
expfactory
software to generate a reproducible container with a battery of experiments
fastdm
Python wrapper for the fast-dm drift diffusion model fitter
glm-hmm
Code to reproduce figures for "Mice alternate between discrete strategies during perceptual decision-making" from Ashwood, Roy, Stone, IBL, Churchland, Pouget and Pillow (2021)
hBayesDM
Hierarchical Bayesian modeling of RLDM tasks, using R & Python
importance_sampler
Using importance sampling to calcualte margnial likelihood for a simple hyperbolic model in intertemporal choice task
method_HtSSM_aDDM
Method to fit the a hierarchical time-varying sequential sampling and an attentional drift diffusion model.
neuromatch-2021
My code from neuromatch academey 2021
NH19-Visualization
A collection of notebooks demonstrating plotting with matplotlib
Pandas_Advanced_Exercise
Pandas进阶修炼300题
PRML_learning
learning fomula
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Python-Code-for-Ten-rules
Ten simple rules for the computational modeling of behavioral data
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
QuantCog
Introduction to Quantified Cognition
sbi
Simulation-based inference toolkit
Sepulveda_et_al_2020
Datasets and code presented in Sepulveda et al., 2020. Visual attention modulates the integration of goal-relevant evidence and not value, eLife (https://elifesciences.org/articles/60705)