output
20172026
most citedTowards the determination of heavy-quark transport coefficients in quark-gluon plasma

160 citations

Showing cs.NEShow all

5 papers · 1 filter

cs.NE2025

()-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces

Tingyang Wei, Jiao Liu, Abhishek Gupta +2

Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering a non-fixed and potentially infinite…

cs.NE2025★ 8 cited

Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities

Jian Cheng Wong, Abhishek Gupta, Chin Chun Ooi +3

Deep learning models trained on finite data lack a complete understanding of the physical world. On the other hand, physics-informed neural networks (PINNs) are infused with such k…

cs.NE2024★ 20 cited

Machine Learning Driven Global Optimisation Framework for Analog Circuit Design

Ria Rashid, Komala Krishna, Clint Pazhayidam George +1

We propose a machine learning-driven optimisation framework for analog circuit design in this paper. The primary objective is to determine the device sizes for the optimal performa…

cs.NE2023★ 1 cited

Evolutionary Optimization of Physics-Informed Neural Networks: Advancing Generalizability by the Baldwin Effect

Jian Cheng Wong, Chin Chun Ooi, Abhishek Gupta +4

Physics-informed neural networks (PINNs) are at the forefront of scientific machine learning, making possible the creation of machine intelligence that is cognizant of physical law…

cs.NE2023★ 12 cited

Performance Evaluation of Evolutionary Algorithms for Analog Integrated Circuit Design Optimisation

Ria Rashid, Gopavaram Raghunath, Vasant Badugu +1

An automated sizing approach for analog circuits using evolutionary algorithms is presented in this paper. A targeted search of the search space has been implemented using a partic…