3 papers
cs.LG2026
Hierarchical rank-evolving representation for physics-informed neural networks
Ruoyang Su, Xi-Le Zhao, Kun Li +1
Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental challenge: they mainly rely…
cs.CV2026
TenExp: Mixture-of-Experts-Based Tensor Decomposition Structure Search Framework
Ting-Wei Zhou, Xi-Le Zhao, Sheng Liu +3
Recently, tensor decompositions continue to emerge and receive increasing attention. Selecting a suitable tensor decomposition to exactly capture the low-rank structures behind the…
cs.CV2026
Neural Operator-Grounded Continuous Tensor Function Representation and Its Applications
Ruoyang Su, Xi-Le Zhao, Sheng Liu +3
Recently, continuous tensor functions have attracted increasing attention, because they can unifiedly represent data both on mesh grids and beyond mesh grids. However, since mode-$…