7 citations · 7 across the 6 of their papers we have counts for
3 papers · 1 filter
Graphical conditional generative modeling for digital twin modeling
Zongren Zou, Théo Bourdais, Ricardo Baptista +1
Digital twin modeling, including control and data assimilation under model uncertainty, often faces an open-ended fidelity problem: adding variables, data streams, and time scales…
Pruning Deep Neural Networks via the Marchenko--Pastur Distribution
Leonid Berlyand, Theo Bourdais, Houman Owhadi +1
We study a Marchenko--Pastur (MP) random-matrix approach to pruning deep neural networks with very small post-pruning fine-tuning budgets. The main practical contribution is accura…
ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks
Zhizhen Zhang, Hyemin Gu, Benjamin J. Zhang +6
Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce ISOMORPH, the first public di…