369 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nanyang Technological UniversitySG25 papers
- Agency for Science, Technology and ResearchSG23 papers
- National University of SingaporeSG9 papers
- Institute of High Performance ComputingSG6 papers
- Massachusetts Institute of TechnologyUS6 papers
- Center for Free-Electron Laser ScienceDE4 papers
- Technion – Israel Institute of TechnologyIL4 papers
- Hamburg Centre for Ultrafast Imaging3 papers
- Shandong UniversityCN3 papers
- Chinese University of Hong KongHK2 papers
- Deutsches Elektronen-Synchrotron DESYDE2 papers
- Institute of Materials Research and EngineeringSG2 papers
56 papers
PINEAPPLE: Physics-Informed Neuro-Evolution Algorithm for Prognostic Parameter Inference in Lithium-Ion Battery Electrodes
Karkulali Pugalenthi, Jian Cheng Wong, Qizheng Yang +4
Accurate, real-time, yet non-destructive estimation of internal states in lithium-ion batteries is critical for predicting degradation, optimizing usage strategies, and extending o…
Multi-modal cross-domain mixed fusion model with dual disentanglement for fault diagnosis under unseen working conditions
Pengcheng Xia, Yixiang Huang, Chengjin Qin +1
Intelligent fault diagnosis has become an indispensable technique for ensuring machinery reliability. However, existing methods suffer significant performance decline in real-world…
()-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…
How do imperfections cause asymmetry in elastic snap-through?
Andrea Giudici, Weicheng Huang, Qiong Wang +4
A symmetrically-buckled arch whose boundaries are clamped at an angle has two stable equilibria: an inverted and a natural state. When the distance between the clamps is increased…
Twisted Fusion Products and Quantum Twisted -Systems
Mingyan Simon Lin
We obtain a complete characterization of the space of matrix elements dual to the graded multiplicity space arising from fusion products of Kirillov-Reshetikhin modules over specia…
In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review
Lequn Chen, Guijun Bi, Xiling Yao +6
Laser Additive Manufacturing (LAM) presents unparalleled opportunities for fabricating complex, high-performance structures and components with unique material properties. Despite…
Celestial Machine Learning: Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman
Zi-Yu Khoo, Gokul Rajiv, Abel Yang +2
Can a machine or algorithm discover or learn the elliptical orbit of Mars from astronomical sightings alone? Johannes Kepler required two paradigm shifts to discover his First Law…
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning
Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan
Many functions characterising physical systems are additively separable. This is the case, for instance, of mechanical Hamiltonian functions in physics, population growth equations…
Celestial Machine Learning: From Data to Mars and Beyond with AI Feynman
Zi-Yu Khoo, Abel Yang, Jonathan Sze Choong Low +1
Can a machine or algorithm discover or learn Kepler's first law from astronomical sightings alone? We emulate Johannes Kepler's discovery of the equation of the orbit of Mars with…
Transient amplification of broken symmetry in elastic snap-through
Qiong Wang, Andrea Giudici, Weicheng Huang +4
A snap-through bifurcation occurs when a bistable structure loses one of its stable states and moves rapidly to the remaining state. For example, a buckled arch with symmetrically…
Multimodal sensor fusion for real-time location-dependent defect detection in laser-directed energy deposition
Lequn Chen, Xiling Yao, Wenhe Feng +2
Real-time defect detection is crucial in laser-directed energy deposition (L-DED) additive manufacturing (AM). Traditional in-situ monitoring approach utilizes a single sensor (i.e…
Prompt Evolution for Generative AI: A Classifier-Guided Approach
Melvin Wong, Yew-Soon Ong, Abhishek Gupta +2
Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with generative AI. However, such models often fa…
In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning
Lequn Chen, Xiling Yao, Chaolin Tan +6
Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlyi…
Identifying the Key Attributes in an Unlabeled Event Log for Automated Process Discovery
Kentaroh Toyoda, Rachel Gan Kai Ying, Allan NengSheng Zhang +1
Process mining discovers and analyzes a process model from historical event logs. The prior art methods use the key attributes of case-id, activity, and timestamp hidden in an even…
Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results
Nicholas Sung Wei Yong, Jian Cheng Wong, Pao-Hsiung Chiu +3
The potential of learned models for fundamental scientific research and discovery is drawing increasing attention worldwide. Physics-informed neural networks (PINNs), where the los…
Autonomous Cross Domain Adaptation under Extreme Label Scarcity
Weiwei Weng, Mahardhika Pratama, Choiru Za'in +4
A cross domain multistream classification is a challenging problem calling for fast domain adaptations to handle different but related streams in never-ending and rapidly changing…
Efficient Neural Neighborhood Search for Pickup and Delivery Problems
Yining Ma, Jingwen Li, Zhiguang Cao +4
We present an efficient Neural Neighborhood Search (N2S) approach for pickup and delivery problems (PDPs). In specific, we design a powerful Synthesis Attention that allows the van…
Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
Jingwen Li, Yining Ma, Ruize Gao +4
Existing deep reinforcement learning (DRL) based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with homogeneous vehicle fleet, in which the…
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
Jian Cheng Wong, Chinchun Ooi, Abhishek Gupta +1
A physics-informed neural network (PINN) uses physics-augmented loss functions, e.g., incorporating the residual term from governing partial differential equations (PDEs), to ensur…
Continual Learning via Inter-Task Synaptic Mapping
Mao Fubing, Weng Weiwei, Mahardhika Pratama +1
Learning from streaming tasks leads a model to catastrophically erase unique experiences it absorbs from previous episodes. While regularization techniques such as LWF, SI, EWC hav…
Deep Learning-Aided OFDM-Based Generalized Optical Quadrature Spatial Modulation
Chen Chen, Lin Zeng, Xin Zhong +3
In this paper, we propose an orthogonal frequency division multiplexing (OFDM)-based generalized optical quadrature spatial modulation (GOQSM) technique for multiple-input multiple…
Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances
Mojtaba Shakeri, Erfan Miahi, Abhishek Gupta +1
In today's digital world, we are faced with an explosion of data and models produced and manipulated by numerous large-scale cloud-based applications. Under such settings, existing…
Grasping Detection Network with Uncertainty Estimation for Confidence-Driven Semi-Supervised Domain Adaptation
Haiyue Zhu, Yiting Li, Fengjun Bai +6
Data-efficient domain adaptation with only a few labelled data is desired for many robotic applications, e.g., in grasping detection, the inference skill learned from a grasping da…
Data-Driven Multi-Objective Controller Optimization for a Magnetically-Levitated Nanopositioning System
Xiaocong Li, Haiyue Zhu, Jun Ma +4
The performance achieved with traditional model-based control system design approaches typically relies heavily upon accurate modeling of the motion dynamics. However, modeling the…