Software

Partially observable Markov decision process framework for operating condition optimization using real-time degradation signals
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
Personalized Tucker decomposition modeling commonality and peculiarity on tensor data.
Probabilistic Kolmogorov-Arnold Networks via sparsified deep Gaussian processes with additive kernels
Probabilistic Kolmogorov-Arnold Networks via sparsified deep Gaussian processes with additive kernels
Image-based novel fault detection with deep learning classifiers using hierarchical labels
Novel fault detection in images with hierarchical deep learning labels.
Project
Leveraging pretrained transformers for efficient segmentation and lesion detection in cone-beam computed tomography scans
Leveraging pretrained transformers for efficient segmentation and lesion detection in cone-beam computed tomography scans
Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information
PV generation forecasting by fusing multi-source information with dynamic Bayesian networks.
Project DOI
Sparse decomposition methods for spatio-temporal anomaly detection
Sparse decomposition methods for spatio-temporal anomaly detection
Thompson sampling-based partially observable online change detection for exponential families
Thompson sampling for partially observable online change detection.
Project
Uncertainty-based active learning by bayesian U-Net for multi-label cone-beam CT segmentation
Uncertainty-based active learning by bayesian U-Net for multi-label cone-beam CT segmentation
DOE / Nuclear, Bayesian Optimization for Automatic Reactor Design Optimization
Bayesian optimization for reactor design