AlexanderFengler

Alexander Fengler's repositories

hddmnn_tutorial

Code for a Tutorial on using the Neural Network Extension of HDDM

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LANfactory

Package to Train LANs (Likelihood approximation networks)

Language:Jupyter NotebookMIT11 5 7

ssm-simulators

Python Package which collects simulators for Sequential Sampling Models

Language:Jupyter NotebookMIT11 5 24

hddmnn_tutorial_paper

Scripts and Tutorial as in the Tutorial Paper for HDDM

Language:Jupyter NotebookMIT4 30

hddm_workshop

Material for a basic HDDM Tutorial Workshop

Language:Jupyter NotebookMIT3 20

ssmjax

Jax based samplers for sequential sampling models

Language:Jupyter NotebookMIT3 2 6

LAN_scripts

Scripts for end-to-end training of LANs and other convenience functions

Language:Jupyter NotebookMIT2 40

hddm

HDDM is a python module that implements Hierarchical Bayesian parameter estimation of Drift Diffusion Models (via PyMC).

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LAN_pipeline_minimal

Minimal version of the LAN pipeline for internal purposes

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AlexanderFengler.github.io

Personal Webpage

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LAN_varinf

Scripts for a project that compares performances of LANs across inference algorithms

Language:Jupyter NotebookMIT020

bambi

BAyesian Model-Building Interface (Bambi) in Python.

Language:PythonMIT010

BayesFlow

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

Language:PythonMIT010

blog_posts

Repo with intended Blog Posts.

Language:Jupyter NotebookMIT020

cbm_py

Implements HBI algorithms from Piray et. al. (2019)

MIT030

clash_of_worlds

Github repository for working paper: A clash between worlds: Posterior Amortization and the Scientific Workflow

Language:Jupyter NotebookMIT030

dynddm

Code for project in which drift depends on dynamical systems

Language:Jupyter NotebookMIT020

hierarchical_decision_making

Code concerning the data analysis project on a hierarchical decision making task

Language:Jupyter NotebookMIT040

HyGene.jl

Model of hypothesis generation by Thomas et al. (2008)

MIT000

kabuki

Kabuki is a Python toolbox that allows easy creation of hierarchical Bayesian models for the cognitive sciences.

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lan_alternatives

Testing LAN alternatives

MIT030

lqg

Inverse optimal control for continuous psychophysics

Language:Jupyter NotebookAGPL-3.0010

minimc

Just a little MCMC

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Omission_omission

Study on the effect of ignoring omissions

Language:Jupyter NotebookMIT000

PACT-public

Data, analyses, and figures for 'Humans reconfigure target and distractor processing to address distinct task demands'

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pybeam

PyBEAM: A Bayesian approach to parameter inference for a wide class of binary evidence accumulation models

Language:Jupyter NotebookMIT010

pymc

Bayesian Modeling and Probabilistic Programming in Python

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read_the_docs_test

Testing read the docs

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reverie

:art: A ridiculously elegant Jekyll theme.

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RL-SSM

RL-SSM work

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