arXiv Machine Learning By Mohamed Gharib, Leonid Popryho, Inna Partin-Vaisband

From Physics to Surrogate Intelligence: A Unified Electro-Thermo-Optimization Framework for TSV Networks

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arXiv:2603. 29268v2 Announce Type: replace Abstract: High-density through-substrate vias (TSVs) enable 2.

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arXiv Machine Learning
Jun 8

Amortized Neural Optimization for Pre-Layout Signal Integrity Design Space Exploration using Differentiable Surrogates

arXiv:2606. 07463v1 Announce Type: cross Abstract: Pre-layout design space exploration (DSE) for high-speed signal integrity (SI) analysis is often limited by the computational cost of simulations and iterative optimization algorithms within modern electronic design automation (EDA) workflows.

By Julian With\"oft, Werner John, Emre Ecik, Ralf Br\"uning, J\"urgen G\"otze
arXiv Machine Learning
Jun 19

A Hybrid GNN-FEM Framework for Phase-Field Fracture Simulation. Physics-Preserving Hybridization for Generalizable Surrogate Modeling

arXiv:2606. 19378v1 Announce Type: new Abstract: Scientific machine learning (SciML) has emerged as a promising approach for accelerating simulations of complex physical systems, yet achieving physically consistent and generalizable predictions for nonlinear, history-dependent problems remains a central challenge.

By Hyeonbin Moon, Yongjin Choi, Seunghwa Ryu