Deep convolutional neural networks for uncertainty propagation in random fields. - Xihaier Luo; Ahsan Kareem (Comput. Aided Civ. Infrastructure Eng., 2019)

Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data. - Xihaier Luo; Ahsan Kareem (CoRR, 2019)

Probabilistic Evolution of Stochastic Dynamical Systems: A Meso-scale Perspective. - Chao Yin; Xihaier Luo; Ahsan Kareem (CoRR, 2020)

Feature Importance in a Deep Learning Climate Emulator. - Wei Xu 020; Xihaier Luo; Yihui Ren 001; Ji Hwan Park; Shinjae Yoo; Balasubramanya T. Nadiga (CoRR, 2021)

Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. - Xihaier Luo; Sean McCorkle; Gilchan Park; Vanessa López-Marrero; Shinjae Yoo; Edward R. Dougherty; Xiaoning Qian; Francis J. Alexander; Byung-Jun Yoon (BIBM, 2022)

A Machine Learning-based Characterization Framework for Parametric Representation of Nonlinear Sloshing. - Xihaier Luo; Ahsan Kareem; Liting Yu; Shinjae Yoo (CoRR, 2022)

A Bayesian Deep Learning Approach to Near-Term Climate Prediction. - Xihaier Luo; Balasubramanya T. Nadiga; Yihui Ren 001; Ji Hwan Park; Wei Xu 020; Shinjae Yoo (CoRR, 2022)

Automated Extraction of Molecular Interactions and Pathway Knowledge using Large Language Model, Galactica: Opportunities and Challenges. - Gilchan Park; Byung-Jun Yoon; Xihaier Luo; Vanessa López-Marrero; Patrick R. Johnstone; Shinjae Yoo; Francis J. Alexander (BioNLP@ACL, 2023)

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing. - Xihaier Luo; Ahsan Kareem; Shinjae Yoo (CoRR, 2023)

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge. - Gilchan Park; Byung-Jun Yoon; Xihaier Luo; Vanessa López-Marrero; Patrick R. Johnstone; Shinjae Yoo; Francis J. Alexander (CoRR, 2023)

Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks. - Xihaier Luo; Wei Xu 020; Balu Nadiga; Yihui Ren 001; Shinjae Yoo (ICLR, 2024)

Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution. - Xihaier Luo; Xiaoning Qian; Byung-Jun Yoon (ICML, 2024)

Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data. - Alif Bin Abdul Qayyum; Xihaier Luo; Nathan M. Urban; Xiaoning Qian; Byung-Jun Yoon (MLSP, 2024)

GAN-based Extreme Conditional Distribution Estimation for Renewable Energy Systems. - Guang Zhao; Xihaier Luo; Shinjae Yoo; Nicole D. Jackson (SmartGridComm, 2024)

Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data. - Alif Bin Abdul Qayyum; Xihaier Luo; Nathan M. Urban; Xiaoning Qian; Byung-Jun Yoon (CoRR, 2024)

Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction. - Wei Xu 020; Derek Freeman DeSantis; Xihaier Luo; Avish Parmar; Klaus Tan; Balu Nadiga; Yihui Ren 001; Shinjae Yoo (CoRR, 2024)

Variable Rate Neural Compression for Sparse Detector Data. - Yi Huang 019; Yeonju Go; Jin Huang; Shuhang Li; Xihaier Luo; Thomas Marshall; Joseph D. Osborn; Christopher Pinkenburg; Yihui Ren 001; Evgeny Shulga; Shinjae Yoo; Byung-Jun Yoon (CoRR, 2024)

Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance Sampling. - Xihaier Luo; Samuel Lurvey; Yi Huang 019; Yihui Ren 001; Jin Huang; Byung-Jun Yoon (CoRR, 2024)

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events. - Ayush Khot; Xihaier Luo; Ai Kagawa; Shinjae Yoo (CoRR, 2024)

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation. - Xihaier Luo; Seyednami Niyakan; Patrick R. Johnstone; Sean McCorkle; Gilchan Park; Vanessa López-Marrero; Shinjae Yoo; Edward R. Dougherty; Xiaoning Qian; Francis J. Alexander; Shantenu Jha; Byung-Jun Yoon (Frontiers Bioinform., 2024)

Density estimation via measure transport: Outlook for applications in the biological sciences. - Vanessa López-Marrero; Patrick R. Johnstone; Gilchan Park; Xihaier Luo (Stat. Anal. Data Min., 2024)

Scale-Invariant Implicit Neural Representations For Object Counting. - Siyuan Xu; Yucheng Wang; Xihaier Luo; Byung-Jun Yoon; Xiaoning Qian (CVPR Workshops, 2025)

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge. - Gilchan Park; Byung-Jun Yoon; Xihaier Luo; Vanessa López-Marrero; Shinjae Yoo; Shantenu Jha (J. Comput. Biol., 2025)

GST-UNet: Spatiotemporal Causal Inference with Time-Varying Confounders. - Miruna Oprescu; David Keetae Park; Xihaier Luo; Shinjae Yoo; Nathan Kallus (CoRR, 2025)

Generalizable Implicit Neural Representations via Parameterized Latent Dynamics for Baroclinic Ocean Forecasting. - Guang Zhao; Xihaier Luo; Seungjun Lee; Yihui Ren 001; Shinjae Yoo; Luke Van Roekel; Balu Nadiga; Sri Hari Krishna Narayanan; Yixuan Sun; Wei Xu 020 (CoRR, 2025)

SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields. - David Keetae Park; Xihaier Luo; Guang Zhao; Seungjun Lee; Miruna Oprescu; Shinjae Yoo (CoRR, 2025)

STACI: Spatio-Temporal Aleatoric Conformal Inference. - Brandon R. Feng; David Keetae Park; Xihaier Luo; Arantxa Urdangarin; Shinjae Yoo; Brian J. Reich (CoRR, 2025)

Explorable INR: An Implicit Neural Representation for Ensemble Simulation Enabling Efficient Spatial and Parameter Exploration. - Yi-Tang Chen; Haoyu Li; Neng Shi; Xihaier Luo; Wei Xu 020; Han-Wei Shen (IEEE Trans. Vis. Comput. Graph., 2025)

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics. - David Keetae Park; Shuhang Li; Yi Huang 019; Xihaier Luo; Haiwang Yu; Yeonju Go; Christopher Pinkenburg; Yuewei Lin; Shinjae Yoo; Joseph D. Osborn; Jin Huang; Yihui Ren 001 (CoRR, 2025)