222 citations · 872 across the 41 of their papers we have counts for
42 papers
Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
Chuang Ma, Tomoyuki Obuchi, Toshiyuki Tanaka
A phenomenon known as ''Neural Collapse (NC)'' in deep classification tasks, in which the penultimate-layer features and the final classifiers exhibit an extremely simple geometric…
Universality of reservoir systems with recurrent neural networks
Hiroki Yasumoto, Toshiyuki Tanaka
Approximation capability of reservoir systems whose reservoir is a recurrent neural network (RNN) is discussed. We show what we call uniform strong universality of RNN reservoir sy…
Spatio-temporal reconstruction of substance dynamics using compressed sensing in multi-spectral magnetic resonance spectroscopic imaging
Utako Yamamoto, Hirohiko Imai, Kei Sano +3
The objective of our study is to observe dynamics of multiple substances in vivo with high temporal resolution from multi-spectral magnetic resonance spectroscopic imaging (MRSI) d…
Label Smoothing is Robustification against Model Misspecification
Ryoya Yamasaki, Toshiyuki Tanaka
Label smoothing (LS) adopts smoothed targets in classification tasks. For example, in binary classification, instead of the one-hot target used in conventional logisti…
Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models
Daiki Miyake, Akihiro Iohara, Yu Saito +1
In image editing employing diffusion models, it is crucial to preserve the reconstruction fidelity to the original image while changing its style. Although existing methods ensure…
Convergence Analysis of Mean Shift
Ryoya Yamasaki, Toshiyuki Tanaka
The mean shift (MS) algorithm seeks a mode of the kernel density estimate (KDE). This study presents a convergence guarantee of the mode estimate sequence generated by the MS algor…