11 papers
Whole-Body Semantic-to-Actuation Grounding of Elephant-Inspired Soft-Trunk Motion via Lightweight Flow Matching
Tingcong Liu, Tongshun Chen, Siyi Ma +6
For close-contact human-robot interaction (HRI), trunk-like continuum manipulators provide a physical channel for diverse whole-body expression, but grounding open-vocabulary respo…
Do Reviews Matter for Recommendations in the Era of Large Language Models?
Chee Heng Tan, Huiying Zheng, Jing Wang +5
With the advent of large language models (LLMs), the landscape of recommender systems is undergoing a significant transformation. Traditionally, user reviews have served as a criti…
Physics Informed Generative Models for Magnetic Field Images
Aye Phyu Phyu Aung, Lucas Lum, Zhansen Shi +5
In semiconductor manufacturing, defect detection and localization are critical to ensuring product quality and yield. While X-ray imaging is a reliable non-destructive testing meth…
A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy
J. Senthilnath, Jayasanker Jayabalan, Zhuoyi Lin +5
The development of advanced packaging is essential in the semiconductor manufacturing industry. However, non-destructive testing (NDT) of advanced packaging becomes increasingly ch…
3D Magnetic Inverse Routine for Single-Segment Magnetic Field Images
J. Senthilnath, Chen Hao, F. C. Wellstood
In semiconductor packaging, accurately recovering 3D information is crucial for non-destructive testing (NDT) to localize circuit defects. This paper presents a novel approach call…
SG-NNP: Species-separated Gaussian Neural Network Potential with Linear Elemental Scaling and Optimized Dimensions for Multi-component Materials
Ji Wei Yoon, Bangjian Zhou, J Senthilnath
Accurate simulations of materials at long-time and large-length scales have increasingly been enabled by Machine-learned Interatomic Potentials (MLIPs). There have been increasing…
Self-evolving Autoencoder Embedded Q-Network
J. Senthilnath, Bangjian Zhou, Zhen Wei Ng +7
In the realm of sequential decision-making tasks, the exploration capability of a reinforcement learning (RL) agent is paramount for achieving high rewards through interactions wit…
Evolving Restricted Boltzmann Machine-Kohonen Network for Online Clustering
J. Senthilnath, Adithya Bhattiprolu, Ankur Singh +4
A novel online clustering algorithm is presented where an Evolving Restricted Boltzmann Machine (ERBM) is embedded with a Kohonen Network called ERBM-KNet. The proposed ERBM-KNet e…
Bayesian optimized physics-informed neural network for estimating wave propagation velocities
Mahindra Rautela, S. Gopalakrishnan, J. Senthilnath
In this paper, we propose a novel inverse parameter estimation approach called Bayesian optimized physics-informed neural network (BOPINN). In this study, a PINN solves the partial…
Tackling Data Scarcity with Transfer Learning: A Case Study of Thickness Characterization from Optical Spectra of Perovskite Thin Films
Siyu Isaac Parker Tian, Zekun Ren, Selvaraj Venkataraj +13
Transfer learning increasingly becomes an important tool in handling data scarcity often encountered in machine learning. In the application of high-throughput thickness as a downs…
Acceleration based PSO for Multi-UAV Source-Seeking
Adithya Shankar, Harikumar Kandath, J. Senthilnath
This paper presents a novel algorithm for a swarm of unmanned aerial vehicles (UAVs) to search for an unknown source. The proposed method is inspired by the well-known PSO algorith…