Repo for Yale Applied Empirical Methods PHD Course

A Julia rewrite of Dynare: solving, simulating and estimating DSGE models.

A one stop repository for generative AI research updates, interview resources, notebooks and much more!

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

LaTeX source and PDF slides for "Monetary Economics and Policy" by Pierpaolo Benigno, Marcos Consuegra Lopez, and Severin Rothen.

Practical course about Large Language Models.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Understanding Deep Learning - Simon J.D. Prince

A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond

EPFL Machine Learning Course, Fall 2025

Econ 6905 "Topics in Trade" PhD class at Columbia University

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Linux/OSX/FreeBSD resource monitor

Public code for running Stochastic Gradient Descent on GPs.

Code for "Fiscal and Monetary Policy with Heterogeneous Agents" (Auclert, Rognlie, Straub 2025)

Repository supporting the implementation of FAIR principles in the IPCC-WGI Atlas

Course on 'Climate macroeconomics and finance' - University of Bologna

Lecture and conference materials for the DSE2024 at University of Wisconsin-Madison

Code for the Goethe Heterogeneous-Agent Macro Workshop, June 2024

Pen and paper exercises in machine learning

Deep Learning with TensorFlow 2 and Keras, published by Packt

"Computational Methods for Economists using Python", by Richard W. Evans. Tutorials and executable code in Python for the most commonly used computational methods in economics.

"Computational Methods for Economists using Python", by Richard W. Evans. Tutorials and executable code in Python for the most commonly used computational methods in economics.

Example codes for the SIAM Journal on Scientific Computing (SISC) paper "High-Dimensional Dynamic Stochastic Model Representation"

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Lectures and conference materials for the DSE2023 at the University of Lausanne, Switzerland