A comparative analysis of linear regression vs. deep learning models for emulating climate models in the presence of internal variability. (public)
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Updated
Aug 8, 2024 - Jupyter Notebook
A comparative analysis of linear regression vs. deep learning models for emulating climate models in the presence of internal variability. (public)
This repository provides an implementation of algorithmic support for dynamic pricing based on surrogate ticket demand modeling for a passenger rail company on open data.
Python code for running the numerical experiments in the paper "Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods" by Brian Irwin, Eldad Haber, Raviv Gal, and Avi Ziv.
A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives
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