Workshops and Seminars

This workshop explores simulation for economic analysis, demonstrating how to accelerate simulations using modern Python tools. It focuses on Thomas Schelling's segregation model as a running example, with implementations using NumPy, Numba, and JAX.

Scientific computing has advanced rapidly in recent years, driven in large part by demand from and investment in artificial intelligence hardware and software. This workshop explores new computing environments and their features, including parallelization, automatic differentiation, and just-in-time compilers, and investigates how such tools might be applied to macroeconomic applications.

Several important new scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence. This workshop provides an overview of these environments and their features, including automatic differentiation, parallel computing, and just-in-time compilers, and discusses how these tools might be applied to economic applications.

Open source scientific computing environments built around the Python programming language have expanded rapidly in recent years. They now form the dominant paradigm in artificial intelligence and many fields within the natural sciences. This course will cover the foundations of Python programming and Python scientific libraries, and also investigate how Python is being used as the major language of AI.

The recent surge in artificial intelligence research and investment has driven emergence of groundbreaking scientific computing environments, each equipped with advanced features like automatic differentiation, parallel computing capabilities, and just-in-time compilation. This workshop explores their potential applications within economic research.

Several important new scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence. This workshop provides a brief overview of these environments and their features, including automatic differentiation, parallel computing, and just-in-time compilers.

Several important new scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence. This workshop discusses how these tools can be applied to a range of economic applications.