https://github.com/quantecon/rba_workshop_2024

RBA seminar 2024
https://github.com/quantecon/rba_workshop_2024

Last synced: over 1 year ago
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RBA seminar 2024

• Host: GitHub
• URL: https://github.com/quantecon/rba_workshop_2024
• Owner: QuantEcon
• License: mit
• Created: 2024-11-07T05:45:13.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-22T00:33:44.000Z (over 1 year ago)
• Last Synced: 2025-02-23T14:28:41.120Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 17.1 MB
• Stars: 2
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
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# The AI-driven Revolution in Scientific Computing

## RBA Nov 2024

## Abstract

Several important new scientific computing environments have appeared in recent

years, generated by demand from and investment in artificial intelligence. This

workshop will provide a brief overview of these environments and their features,

including automatic differentiation, parallel computing, and just-in-time

compilers. We will discuss how these tools can be applied to a range of economic

applications.  When possible, attendees should bring laptops to the seminar.

## Details

* Instructure: [John Stachurski](https://johnstachurski.net/) (Australian National University).

* Date: November 22nd 2024

## Topics

* An overview of modern scientific computing

* AI and its impact on economic modeling

* Quick introduction to Python

* Accelerating Python using Numba and Fortran

* Automatic differentiation

* Introduction to JAX and GPU computing

* Gini coefficients and Lorenz curves

## Links

* https://github.com/JaxGaussianProcesses/GPJax

* https://github.com/google-deepmind/optax

* https://github.com/ott-jax/ott

* https://github.com/dipolar-quantum-gases/jaxfit

* https://github.com/n2cholas/awesome-jax?tab=readme-ov-file

* https://flax.readthedocs.io/