Publications

A complete list is in my CV and on Google Scholar. Below are my papers from 2025 and 2026; many are joint work with the students I mentor.

2026

Chen, S., Moradi, M., Paynabar, K., Yan, H., 2026, “Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models”, Advances in Neural Information Processing Systems (NeurIPS), 2026, accepted. arXiv:2605.23070.
Feng, S., Yan, H., 2026, “Structurally Separated DAG Learning with Multi-Scale Normalized Closure”, Advances in Neural Information Processing Systems (NeurIPS), 2026, accepted.
Chen, S., Yan, H., 2026, “D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentation”, In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 34755-34764).
Xu, B., Zou, Q., Yang, S., Yan, H., 2026, “Path-Coupled Bellman Flows for Distributional Reinforcement Learning”, Proceedings of the 43rd International Conference on Machine Learning, Seoul, South Korea, PMLR 306, 2026. arXiv:2605.08253.
Xu, B., Yan, H., Reisi-Gahrooei, M., Ilbeigi, M., 2026, “Adaptive Sampling for Automated Post-Disaster Rapid Damage Assessment via Level-Set Cost-Aware Bayesian Optimization”, Proceedings of the SIAM International Conference on Data Mining (SDM). arXiv:2608.02868.
Erly, S., Yan, H., Holte, S., Mei, Y., Kerani, R.P., 2026, “Evaluating Time-Space Methodologies to Detect Clusters of HIV Transmission: A Comparison of Advanced Methods in Washington State, 2010–2022”, Journal of Acquired Immune Deficiency Syndromes, 101(9), 957-963.
Lee, Y., Chen, R.Q., Yan, H., Mupparapu, M., Lure, F., Li, J., Setzer, F.C., 2026, “Dentin-Normalized CBCT Radiomics within a Periapical Lesion Differential Diagnosis System for Differentiating Granulomas and Radicular Cysts”, Journal of Endodontics.
Rathnakumar, R., Lu, X., Huang, J., Yan, H., Liu, Y., 2026, “Bayesian Entropy Neural Networks for physics-aware prediction”, Reliability Engineering & System Safety, 266, 111575.
Wang, A., Yan, H., Du, J., 2026, “Interpretation and visualization of distance covariance with additive decomposition of correlations formula”, INFORMS Journal on Data Science, 2026. DOI: 10.1287/ijds.2024.0054
Kang, Y., Zhao, X., Feng, S., Yan, H., 2026, “Optimizing Multiple Condition Policy based on Real-time Degradation Signals via Model-based Reinforcement Learning”, Journal of Quality Technology.
Huang, J., Li, J., Setzer, F.C., Lure, F., Ju, F., Yan, H., 2026, “Aleatoric-Aware Posterior Regularized Bayesian Neural Networks for Incorporating Domain Knowledge: Addressing Epistemic and Aleatoric Uncertainties”, INFORMS Journal on Data Science, accepted.
Xu, B., Chen, S., Yan, H., 2026, “Retimed Bellman Flows: Escaping the Impossible Triangle of Velocity Bootstrapping”. arXiv preprint arXiv:2609.32828.
Xie, X., Yan, H., 2026, “Personalized Federated Hierarchical Gaussian Processes for Privacy-Preserving Modeling of Heterogeneous Distributed Systems”. arXiv preprint arXiv:2609.19337.
Yan, H., Sarabi, A., Zou, Q., Xu, B., 2026, “General Value Functions for Remaining Useful Life and Failure-Mode Prediction”. arXiv preprint arXiv:2607.22268.

2025

Huang, J., Xu, B., Liu, Y., Yan, H., 2025, “Multi-modal Generative Modeling of Event Sequences and Time Series for Solar PV Systems”, In 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE) (pp. 345-350).
Zou, Q., Yan, H., 2025, “Probabilistic Kolmogorov-Arnold Networks via sparsified deep Gaussian processes with additive kernels”, In 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE) (pp. 2889-2894).
Moradi, M., Chen, S., Yan, H., Paynabar, K., 2025, “A Single Image Is All You Need: Zero-Shot Anomaly Localization Without Training Data”. arXiv preprint arXiv:2509.18354.
Chen, K., Xie, X., German, P., Yan, H., Wang, A., 2025, “Bayesian Optimization for Reactor Design Optimization”, Transactions of the American Nuclear Society.
Shi, N., Yan, H., Guo, S., Al Kontar, R., 2025, “Diffusion-Based Surrogate Modeling and Multi-Fidelity Calibration”, IEEE Transactions on Automation Science and Engineering.
Zhao, X., Yan, H., Liu, Y., 2025, “Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports”, INFORMS Journal on Data Science, 4(1), 51-66.
Sergin, N. D., Hu, J., Li, Z., Zhang, C., Tsung, F., Yan, H., 2025, “Low-rank robust subspace tensor clustering for metro passenger flow modeling”, INFORMS Journal on Data Science, 4(1), 33-50.
Dhulipala, S.L., German, P., Che, Y., Prince, Z.M., Xie, X., Simon, P.A., Labouré, V.M., Yan, H., 2025, “MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications”, Journal of Computational Science, 102776.
Lee, Y., Kwak, M.G., Chen, R.Q., Yan, H., Mupparapu, M., Lure, F., Setzer, F.C., Li, J., 2025, “Oral-Anatomical Knowledge-Informed Semi-Supervised Learning for 3D Dental CBCT Segmentation and Lesion Detection”, IEEE Transactions on Automation Science and Engineering.
Xu, B., Kang, Y., Zhao, X., Yan, H., Ju, F., 2025, “Partially observable Markov decision process framework for operating condition optimization using real-time degradation signals”, Journal of Quality Technology, 1-26.
Hu, J., Shi, N., Al Kontar, R., Yan, H., 2025, “Personalized tucker decomposition: Modeling commonality and peculiarity on tensor data”, Technometrics, 1-17.