activity
20232026
most citedExploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation

12 citations · 26 across the 8 of their papers we have counts for

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cs.LG2025

Evidential Physics-Informed Neural Networks for Scientific Discovery

Hai Siong Tan, Kuancheng Wang, Rafe McBeth

We present the fundamental theory and implementation guidelines underlying Evidential Physics-Informed Neural Network (E-PINN) -- a novel class of uncertainty-aware PINN. It levera…

cs.LG2025

Evidential Physics-Informed Neural Networks

Hai Siong Tan, Kuancheng Wang, Rafe McBeth

We present a novel class of Physics-Informed Neural Networks that is formulated based on the principles of Evidential Deep Learning, where the model incorporates uncertainty quanti…