Hao Yan
Hao Yan
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Bayesian Entropy Neural Networks for physics-aware prediction
D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentation
Path-Coupled Bellman Flows for Distributional Reinforcement Learning
A Single Image Is All You Need— Zero-Shot Anomaly Localization Without Training Data
Bayesian Optimization for Reactor Design Optimization
Diffusion-Based Surrogate Modeling and Multi-Fidelity Calibration
Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports
Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications
Multi-modal Generative Modeling of Event Sequences and Time Series for Solar PV Systems
Oral-anatomical knowledge-informed semi-supervised learning for 3D dental CBCT segmentation and lesion detection
Partially observable Markov decision process framework for operating condition optimization using real-time degradation signals
Personalized tucker decomposition: Modeling commonality and peculiarity on tensor data
Probabilistic Kolmogorov-Arnold Networks via sparsified deep Gaussian processes with additive kernels
Image-based novel fault detection with deep learning classifiers using hierarchical labels
Leveraging pretrained transformers for efficient segmentation and lesion detection in cone-beam computed tomography scans
Optimizing Multiple Condition Policy Based on Real-time Degradation Signals via Model-based Reinforcement Learning
Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information
Sparse decomposition methods for spatio-temporal anomaly detection
Thompson sampling-based partially observable online change detection for exponential families
Uncertainty-based active learning by bayesian U-Net for multi-label cone-beam CT segmentation
A Bayesian partially observable online change detection approach with Thompson sampling
Adaptive resources allocation CUSUM for binomial count data monitoring with application to COVID-19 hotspot detection
ANTLER: Bayesian nonlinear tensor learning and modeler for unstructured, varying-size point cloud data
ANTLER: Bayesian Nonlinear Tensor Learning and Modeler for Unstructured, Varying-Size Point Cloud Data
Graph-aware Tensor Topic Models for Individualized Passenger Travel Pattern Clustering
Posterior Regularized Bayesian Neural Network incorporating soft and hard knowledge constraints
Tensor dirichlet process multinomial mixture model with graphs for passenger trajectory clustering
Individualized Passenger Travel Pattern Multi-Clustering Based on Graph Regularized Tensor Latent Dirichlet Allocation
A tensor voting-based surface anomaly classification approach by using 3D point cloud data
Attention-based Representation Learning for Time Series with Principal and Residual Space Monitoring
Bayesian spatio-temporal graph transformer network (b-star) for multi-aircraft trajectory prediction
Convolutional neural network-assisted adaptive sampling for sparse feature detection in image and video data
Deep spatio-temporal sparse decomposition for trend prediction and anomaly detection in cardiac electrical conduction
Event Extraction for aviation accident reports through attention-based multi-label classification
Individualized passenger travel pattern multi-clustering based on graph regularized tensor latent Dirichlet allocation
Multi-task learning with latent variation decomposition for multivariate responses in a manufacturing network
Profile decomposition based hybrid transfer learning for cold-start data anomaly detection
Rapid detection of hot-spots via tensor decomposition with applications to crime rate data
Artificial Intelligence for the Computer-Aided Detection of Periapical Lesions in Cone-Beam Computed Tomographic Images
Combining Anatomical Constraints and Deep Learning for 3-D CBCT Dental Image Multi-Label Segmentation
Adaptive Change Point Monitoring for High-Dimensional Data
Data-driven trajectory prediction with weather uncertainties: A Bayesian deep learning approach
Deep Multistage Multi-Task Learning for Quality Prediction and Diagnostics of Multistage Manufacturing Systems
Edge Computing Accelerated Defect Classification Based on Deep Convolutional Neural Network With Application in Rolling Image Inspection
Hierarchical Tree-Based Sequential Event Prediction with Application in the Aviation Accident Report
Image Decomposition-Based Sparse Extreme Pixel-Level Feature Detection Model with Application to Medical Images
Real-Time Detection of Clustered Events in Video-Imaging Data with Applications to Additive Manufacturing
Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders
Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction
AKM2D: An Adaptive Framework for Online Sensing and Anomaly Quantification
Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images
Multi-Sensor Prognostics Modeling for Applications with Highly Incomplete Signals
A multiport power conversion system for the more electric aircraft
Anatomically-Constrained Deep Learning for Automating Dental CBCT Segmentation and Lesion Detection
Comments on— On Active Learning Methods for Manifold Data
Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning
Long-short term spatiotemporal tensor prediction for passenger flow profile
Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes With Heterogeneous Sources of Data
Partially observable online change detection via smooth-sparse decomposition
Performance Evaluation of Production Systems Using Real-Time Machine Degradation Signals
Simultaneous material microstructure classification and discovery via hidden Markov modeling of acoustic emission signals
Spatio-Temporal Anomaly Detection, Diagnostics, and Prediction of the Air-Traffic Trajectory Deviation Using the Convective Weather
Image-Based Process Monitoring via Adversarial Autoencoder with Applications to Rolling Defect Detection
Physics-Based Deep Spatio-Temporal Metamodeling for Cardiac Electrical Conduction Simulation
Structured Point Cloud Data Analysis Via Regularized Tensor Regression for Process Modeling and Optimization
Rapid Detection of Hot-Spot by Tensor Decomposition with Application to Weekly Gonorrhea Data
Semi-supervised constrained hidden Markov model using multiple sensors for remaining useful life prediction and optimal predictive maintenance— For remaining useful life prediction and optimal predictive maintenance
Multiple profiles sensor-based monitoring and anomaly detection
Real-time monitoring of high-dimensional functional data streams via spatio-temporal smooth sparse decomposition
Real-time production performance analysis using machine degradation signals— A two-machine case
Weakly correlated profile monitoring based on sparse multi-channel functional principal component analysis
A wavelet-based penalized mixed-effects decomposition for multichannel profile detection of in-line Raman spectroscopy
Anomaly detection in images with smooth background via smooth-sparse decomposition
Generalized Wavelet Shrinkage of Inline Raman Spectroscopy for Quality Monitoring of Continuous Manufacturing of Carbon Nanotube Buckypaper
High dimensional data analysis for anomaly detection and quality improvement
Point Cloud Data Analysis for Process Modeling and Optimization
Fast wavenumber measurement for accurate and automatic location and quantification of defect in composite
Multiple Sensor Data Fusion for Degradation Modeling and Prognostics Under Multiple Operational Conditions
Frequency Domain Instantaneous Wavenumber Estimation for Damage Quantification in Layered Plate Structures
Image-based process monitoring using low-rank tensor decomposition
A globally attractive cycle driven by sequential bifurcations containing ghost effects in a 3-node yeast cell cycle model
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