crgagne
I am currently a postdoc in Peter Dayan's computational neuroscience group. My research focuses on computational psychiatry and reinforcement learning.
Max Planck Institute for Biological CyberneticsTuebingen, Germany
Pinned Repositories
ambi_gain_loss_shock
bayesian_filters
class_deepRL
cs294_IRL_Project
cvar_jmathpsych_2021
dlab-mixed-models
PLOS_CB_paper_belief_updating_in_anxiety_and_depression
pymc3-tensorflow-and-theano-backends
Within this repo, I altered some of the PyMC3 source code so that it can run on either Theano or TensorFlow backends
twosteps_neurips2021
volatility_paper_elife
crgagne's Repositories
crgagne/volatility_paper_elife
crgagne/cvar_jmathpsych_2021
crgagne/pymc3-tensorflow-and-theano-backends
Within this repo, I altered some of the PyMC3 source code so that it can run on either Theano or TensorFlow backends
crgagne/twosteps_neurips2021
crgagne/ambi_gain_loss_shock
crgagne/bayesian_filters
crgagne/class_deepRL
crgagne/cs294_IRL_Project
crgagne/dlab-mixed-models
crgagne/PLOS_CB_paper_belief_updating_in_anxiety_and_depression
crgagne/cdips_project_recommendation_system
crgagne/convnets_in_python
crgagne/cs188
crgagne/cvar_experiment_modeling
crgagne/GA
make an R package to implement a genetic algorithm for variable selection in regression problems, including both linear regression and GLMs.
crgagne/github_repo
crgagne/google-research
Google Research
crgagne/hierarchical_guassian_filters
crgagne/models
Models and examples built with TensorFlow
crgagne/mvpa_meta_analysis
crgagne/pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
crgagne/quack
Presentations made at the QuACK (Quantitative Analysis & Coding Knowledge) workshops at UC Berkeley.
crgagne/quack_math_stats
crgagne/replotting_Figure_4
crgagne/sagemaker
example for how to use sagemaker to run Bark with a custom docker
crgagne/SKAIG-ERC-Reproduction
crgagne/stat215B
crgagne/stat240
crgagne/stat241
crgagne/tutorials