Guang Lin

Siemens (Germany) — Germany

Decision Sciences · Social Sciences

42h-index6.3kcitations398works3.52yr avg
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Research Topics

Probabilistic and Robust Engineering Design(68), Model Reduction and Neural Networks(68), Gaussian Processes and Bayesian Inference(37), Advanced Numerical Methods in Computational Mathematics(22), Power System Optimization and Stability(19)

Publications398 total

ICP-4D: Bridging Iterative Closest Point and LiDAR Panoptic Segmentation
arXiv (Cornell University)·2025Open Access
ICP-4D: Bridging Iterative Closest Point and LiDAR Panoptic Segmentation
ArXiv.org·2025Open Access
iPINNER: An iterative physics-informed neural network with ensemble Kalman filter
Journal of Computational Physics·2025
Real-time concrete strength monitoring using piezoelectric sensors and deep learning
Nature Communications·2025Open Access
DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning
Journal of Computational Physics·2025
Data-driven Feynman-Kac Discovery with Applications to Prediction and Data Generation
arXiv (Cornell University)·2025Open Access
LES-SINDy: Laplace-enhanced sparse identification of nonlinear dynamical systems
Journal of Computational Physics·2025
Finite Element Representation Network (FERN) for Operator Learning with a Localized Trainable Basis
arXiv (Cornell University)·2025Open Access
A Review of Artificial Intelligence-Driven Approaches for Nanoscale Heat Conduction and Radiation
Journal of Computing and Information Science in Engineering·2025· 1 cited
SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions
arXiv (Cornell University)·2025Open Access
PO-CKAN:Physics Informed Deep Operator Kolmogorov Arnold Networks with Chunk Rational Structure
arXiv (Cornell University)·2025Open Access
Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
arXiv (Cornell University)·2025Open Access
Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct
arXiv (Cornell University)·2025Open Access
Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences·2025· 1 cited
ProTDyn: a foundation Protein language model for Thermodynamics and Dynamics generation
2025Open Access
Low-Rank Adaptation of Evolutionary Deep Neural Networks for Efficient Learning of Time-Dependent PDEs
arXiv (Cornell University)·2025Open Access
A self-adaptive energy-based learning rate for stochastic gradient descent via Vector Auxiliary Variable method
Engineering Applications of Artificial Intelligence·2025
Conformalized prediction of post-fault voltage trajectories using pre-trained and finetuned attention-driven neural operators
Neural Networks·2025
Adversarial guided diffusion models for adversarial purification
Neural Networks·2025· 2 cited
Feature visibility optimization-based interactive modeling for fine-grained image classification
Signal Image and Video Processing·2025
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Frequent Co-authors

George Em Karniadakis(6), Christian Moya(4), Yun Qian(3), Zecheng Zhang(3), Ziyang Huang(3), Arezoo M. Ardekani(3), Jianhai Zhang(2), Wanzeng Kong(2), Sheng Zhang(2), Peng Jiang(2), Huan Xu(2), Zhangshuan Hou(2), L. Ruby Leung(2), Chun Zhao(2), Hailong Wang(2), Minghuai Wang(2), Xiaohong Liu(2), Yixuan Sun(2), Xiu Yang(2), Han‐Wei Shen(2)