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an-introduction-to-bayesian-inference-in-pystan

Code for blog post on Bayesian inference in PyStan

bayesian-cognitive-modeling-in-pymc3

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

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

experiment_practise

expfactory

software to generate a reproducible container with a battery of experiments

fastdm

Python wrapper for the fast-dm drift diffusion model fitter

fitting-ornstein-uhlenbeck-model

template of using probability density approximation to fit ou model

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

machine-learning

makeyourownneuralnetwork

Code for the Make Your Own Neural Network book

method_htssm_addm

Method to fit the a hierarchical time-varying sequential sampling and an attentional drift diffusion model.

mfit

Simple model-fitting tools

mfit_python

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mne-cookbook

使用MNE-python过程中的小技巧,即如何处理MEG/EEG信号数据.

model_comparison

neuromatch-2021

My code from neuromatch academey 2021

nh19-visualization

A collection of notebooks demonstrating plotting with matplotlib

nora_whitakervendetti_devsci2017

Code to reproduce the figures in the NORA manuscript "Neuroscientific insights into the development of analogical reasoning".

optimal-policy-for-value-based-decision-making

These are the codes related to the following publication: Tajima, S., Drugowitsch, J., and Pouget, A. Optimal policy for value-based decision-making. Nature Communications, 7:12400, (2016).

pandas_advanced_exercise

Pandas进阶修炼300题

pieterv_public

posner

The Posner task as a demo for workshop

prml_learning

learning fomula