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stat.ML2026
Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection
Elynn Chen, Jiayu Li, Zheshi Zheng +1
Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across modes carry information that is de…
stat.ML2026
Quantifying Epistemic Uncertainty in Diffusion Models
Aditi Gupta, Raphael A. Meyer, Yotam Yaniv +2
To ensure high quality outputs, it is important to quantify the epistemic uncertainty of diffusion models. Existing methods are often unreliable because they mix epistemic and alea…
stat.ML2024
High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors
Elynn Chen, Yuefeng Han, Jiayu Li
Tensor classification is gaining importance across fields, yet handling partially observed data remains challenging. In this paper, we introduce a novel approach to tensor classifi…