@comp_simon
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In case you haven't come across it yet, this open-source book by @comp_simon on Econ/Finance + AI is an absolute gold mine:View quoted post on X
👉 sischei.github.io/Deep_Learning_…
github.com GitHub - GaussianProcessesForDynamicEcon/DynamicIncentiveProblems Contribute to GaussianProcessesForDynamicEcon/DynamicIncentiveProblems development by creating an account on GitHub. "Machine Learning for Dynamic Incentive Problems": @comp_simon & @PhilippJRenner introduce a framework combining penalties, Gaussian processes and Bayesian active learning to bypass set-valued dynamic programming. Handles at least 10 persistent types."
restud.com/machine-learni…View quoted post on X
Free-access article link: academic.oup.com/restud/advance…View quoted post on X
Python toolbox & replication code: github.com/GaussianProces…
academic.oup.com Machine Learning for Dynamic Incentive Problems Abstract. We present a flexible and scalable computational framework integrating machine learning and optimization theory to solve dynamic adverse selectio We introduce a penalty relaxation that bypasses computing feasible sets a priori, solving it via value function iteration with Gaussian Process regression and Bayesian Active Learning. The generic framework scales up to at least 10 persistent types.View quoted post on X
