GPU-based Ising Computing for Solving Balanced Min-Cut Graph Partitioning Problem. - Chase Cook; Wentian Jin; Sheldon X.-D. Tan (CoRR, 2019)

Accurate Power Density Map Estimation for Commercial Multi-Core Microprocessors. - Jinwei Zhang; Sheriff Sadiqbatcha; Wentian Jin; Sheldon X.-D. Tan (DATE, 2020)

Full-Chip Thermal Map Estimation for Commercial Multi-Core CPUs with Generative Adversarial Learning. - Wentian Jin; Sheriff Sadiqbatcha; Jinwei Zhang; Sheldon X.-D. Tan (ICCAD, 2020)

GridNet: Fast Data-Driven EM-Induced IR Drop Prediction and Localized Fixing for On-Chip Power Grid Networks. - Han Zhou 002; Wentian Jin; Sheldon X.-D. Tan (ICCAD, 2020)

EM-GAN: Data-Driven Fast Stress Analysis for Multi-Segment Interconnects. - Wentian Jin; Sheriff Sadiqbatcha; Zeyu Sun 001; Han Zhou 002; Sheldon X.-D. Tan (ICCD, 2020)

Data-Driven Fast Electrostatics and TDDB Aging Analysis. - Shaoyi Peng; Wentian Jin; Liang Chen 025; Sheldon X.-D. Tan (MLCAD, 2020)

EM-GAN: Fast Stress Analysis for Multi-Segment Interconnect Using Generative Adversarial Networks. - Wentian Jin; Sheriff Sadiqbatcha; Jinwei Zhang; Sheldon X.-D. Tan (CoRR, 2020)

EMGraph: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnect Using Graph Convolution Networks. - Wentian Jin; Liang Chen 025; Sheriff Sadiqbatcha; Shaoyi Peng; Sheldon X.-D. Tan (DAC, 2021)

Data-Driven Electrostatics Analysis based on Physics-Constrained Deep learning. - Wentian Jin; Shaoyi Peng; Sheldon X.-D. Tan (DATE, 2021)

Fast Electrostatic Analysis For VLSI Aging based on Generative Learning. - Subed Lamichhane; Shaoyi Peng; Wentian Jin; Sheldon X.-D. Tan (MLCAD, 2021)

Special Session: Machine Learning for Semiconductor Test and Reliability. - Hussam Amrouch; Animesh Basak Chowdhury; Wentian Jin; Ramesh Karri; Farshad Khorrami; Prashanth Krishnamurthy; Ilia Polian; Victor M. van Santen; Benjamin Tan 001; Sheldon X.-D. Tan (VTS, 2021)

Fast Thermal Analysis for Chiplet Design based on Graph Convolution Networks. - Liang Chen 025; Wentian Jin; Sheldon X.-D. Tan (ASP-DAC, 2022)

HierPINN-EM: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnects Using Hierarchical Physics-Informed Neural Network. - Wentian Jin; Liang Chen 025; Subed Lamichhane; Mohammadamir Kavousi; Sheldon X.-D. Tan (ICCAD, 2022)

Learning Based Spatial Power Characterization and Full-Chip Power Estimation for Commercial TPUs. - Jincong Lu; Jinwei Zhang; Wentian Jin; Sachin Sachdeva; Sheldon X.-D. Tan (ASP-DAC, 2023)

Fast Full-Chip Parametric Thermal Analysis Based on Enhanced Physics Enforced Neural Networks. - Liang Chen 025; Jincong Lu; Wentian Jin; Sheldon X.-D. Tan (ICCAD, 2023)

PostPINN-EM: Fast Post-Voiding Electromigration Analysis Using Two-Stage Physics-Informed Neural Networks. - Subed Lamichhane; Wentian Jin; Liang Chen 025; Mohammadamir Kavousi; Sheldon X.-D. Tan (ICCAD, 2023)

GridNetOpt: Fast Full-Chip EM-Aware Power Grid Optimization Accelerated by Deep Neural Networks. - Han Zhou 002; Yibo Liu; Wentian Jin; Sheldon X.-D. Tan (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Linear Time Electromigration Analysis Based on Physics-Informed Sparse Regression. - Liang Chen 025; Wentian Jin; Mohammadamir Kavousi; Subed Lamichhane; Sheldon X.-D. Tan (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Thermoelectric Cooler Modeling and Optimization via Surrogate Modeling Using Implicit Physics-Constrained Neural Networks. - Liang Chen 025; Wentian Jin; Jinwei Zhang; Sheldon X.-D. Tan (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)