Piecewise Multivariate Polynomials Using a Four-Layer Perceptron. - Yusuke Tanahashi; Kazumi Saito; Ryohei Nakano (KES, 2004)

Finding a succinct multi-layer perceptron having shared weights. - Yusuke Tanahashi; Xiang-Fang Chin; Kazumi Saito; Ryohei Nakano (IJCNN, 2005)

Model Selection and Weight Sharing of Multi-layer Perceptrons. - Yusuke Tanahashi; Kazumi Saito; Ryohei Nakano (KES (4), 2005)

Myelination and long diffusion times alter diffusion-tensor-imaging contrast in myelin-deficient shiverer mice. - Govind Nair; Yusuke Tanahashi; Hoi Pang Low; Susan Billings-Gagliardi; William J. Schwartz; Timothy Q. Duong (NeuroImage, 2005)

Finding Nominally Conditioned Multivariate Polynomials Using a Four-Layer Perceptron Having Shared Weights. - Yusuke Tanahashi; Kazumi Saito; Daisuke Kitakoshi; Ryohei Nakano (KES (2), 2006)

A Set of Linear Regressions with Automatic Nominal Space Partition Using a Four-Layer Perceptron. - Ying Yan; Yusuke Tanahashi; Ryohei Nakano (IMECS, 2007)

Nominally Piecewise Multiple Regression Using a Four-Layer Perceptron. - Yusuke Tanahashi; Daisuke Kitakoshi; Ryohei Nakano (KES (3), 2007)

Bidirectional Clustering of MLP Weights for Finding Nominally Conditioned Polynomials. - Yusuke Tanahashi; Ryohei Nakano (ICANN (2), 2009)

Nominally Conditioned Linear Regression. - Yusuke Tanahashi; Ryohei Nakano; Kazumi Saito (ICANN (3), 2010)