4 papers
When Confidence Lacks Concepts: Interpretable OOD Detection via Representation Perturbations
Anju Chhetri, Pratik Shrestha, Ramesh Rana +3
Deep neural networks have achieved remarkable performance across medical imaging tasks, yet their tendency to overgeneralize under distributional shifts poses a major obstacle to s…
EDA-Schema-V2: A Multimodal Schema, Open Datasets, and Benchmarks for Machine Learning in Digital Physical Design
Pratik Shrestha, Alec Aversa, Ioannis Savidis
The continuous scaling of CMOS technology has significantly increased the complexity of very large-scale integrated circuits, driving interest in applying machine learning (ML) to…
Emerging ML-AI Techniques for Analog and RF EDA
Zhengfeng Wu, Ziyi Chen, Nnaemeka Achebe +3
This survey explores the integration of machine learning (ML) into EDA workflows for analog and RF circuits, addressing challenges unique to analog design, which include complex co…
Deep Representation Learning for Electronic Design Automation
Pratik Shrestha, Saran Phatharodom, Alec Aversa +3
Representation learning has become an effective technique utilized by electronic design automation (EDA) algorithms, which leverage the natural representation of workflow elements…