Validation and applications of GLI Ocean product. - Hiroshi Murakami; Kosei Sasaoka; Kohtaro Hosoda; Mayumi Yoshida; Yasushi Mitomi; Akira Mukaida; Hajime Fukushima; Mitsuhiro Toratani; Robert Frouin; B. Greg Mitchell; Hiroshi Kawamura; Futoki Sakaida; et al. (IGARSS, 2004)

Super resolution: Another computational role of short-range horizontal connection in the primary visual cortex. - Hiroaki Sasaki; Shunji Satoh (Neural Networks, 2009)

Efficient Representation by Horizontal Connection in Primary Visual Cortex. - Hiroaki Sasaki; Shunji Satoh; Shiro Usui (ICONIP (1), 2010)

Neural implementation of coarse-to-fine processing in V1 simple neurons. - Hiroaki Sasaki; Shunji Satoh; Shiro Usui (Neurocomputing, 2010)

Topographic Analysis of Correlated Components. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (ACML, 2012)

A system for visualizing human behavior based on car metaphors. - Hiroaki Sasaki; Tsutomu Terada; Masahiko Tsukamoto (AH, 2013)

Differential Base Pattern Coding for Cache Line Data Compression. - Haruhiko Kaneko; Satoshi Fujii; Hiroaki Sasaki (DCC, 2013)

Correlated topographic analysis: estimating an ordering of correlated components. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (Mach. Learn., 2013)

Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (AISTATS, 2014)

Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density. - Hiroaki Sasaki; Aapo Hyvärinen; Masashi Sugiyama (ECML/PKDD (3), 2014)

Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities. - Hiroaki Sasaki; Voot Tangkaratt; Masashi Sugiyama (ACML, 2015)

Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation. - Hiroaki Sasaki; Yung-Kyun Noh; Masashi Sugiyama (AISTATS, 2015)

Key rate of the B92 quantum key distribution protocol with finite qubits. - Hiroaki Sasaki; Ryutaroh Matsumoto; Tomohiko Uyematsu (ISIT, 2015)

Non-Gaussian Component Analysis with Log-Density Gradient Estimation. - Hiroaki Sasaki; Gang Niu 001; Masashi Sugiyama (AISTATS, 2016)

Modal Regression via Direct Log-Density Derivative Estimation. - Hiroaki Sasaki; Yurina Ono; Masashi Sugiyama (ICONIP (2), 2016)

Direct Density Derivative Estimation. - Hiroaki Sasaki; Yung-Kyun Noh; Gang Niu 001; Masashi Sugiyama (Neural Comput., 2016)

Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation. - Ikko Yamane; Hiroaki Sasaki; Masashi Sugiyama (Neural Comput., 2016)

Whitening-Free Least-Squares Non-Gaussian Component Analysis. - Hiroaki Shiino; Hiroaki Sasaki; Gang Niu 001; Masashi Sugiyama (ACML, 2017)

Least-Squares Log-Density Gradient Clustering for Riemannian Manifolds. - Mina Ashizawa; Hiroaki Sasaki; Tomoya Sakai 001; Masashi Sugiyama (AISTATS, 2017)

Estimating Density Ridges by Direct Estimation of Density-Derivative-Ratios. - Hiroaki Sasaki; Takafumi Kanamori; Masashi Sugiyama (AISTATS, 2017)

Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios. - Hiroaki Sasaki; Takafumi Kanamori; Aapo Hyvärinen; Gang Niu 001; Masashi Sugiyama (J. Mach. Learn. Res., 2017)

Simultaneous Estimation of Nongaussian Components and Their Correlation Structure. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (Neural Comput., 2017)

Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction. - Voot Tangkaratt; Hiroaki Sasaki; Masashi Sugiyama (Neural Comput., 2017)

Anomaly Detection of Roads from Driving Data Using a Statistical Discrepancy Measure. - Kazushi Ikeda; Takatomi Kubo; Hiroaki Sasaki; Masataka Mori; Kentarou Hitomi; Kazuhito Takenaka; Kenji Muto (ITSC, 2018)

Neural-Kernelized Conditional Density Estimation. - Hiroaki Sasaki; Aapo Hyvärinen (CoRR, 2018)

Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities. - Hiroaki Sasaki; Voot Tangkaratt; Gang Niu 001; Masashi Sugiyama (Neural Comput., 2018)

Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning. - Aapo Hyvärinen; Hiroaki Sasaki; Richard E. Turner (AISTATS, 2019)

Robust modal regression with direct log-density derivative estimation. - Hiroaki Sasaki; Tomoya Sakai 001; Takafumi Kanamori (CoRR, 2019)

Direct Log-Density Gradient Estimation with Gaussian Mixture Models and Its Application to Clustering. - Qi Zhang; Hiroaki Sasaki; Kazushi Ikeda (IEICE Trans. Inf. Syst., 2019)

Robust modal regression with direct gradient approximation of modal regression risk. - Hiroaki Sasaki; Tomoya Sakai 001; Takafumi Kanamori (UAI, 2020)

Robust contrastive learning and nonlinear ICA in the presence of outliers. - Hiroaki Sasaki; Takashi Takenouchi; Ricardo Pio Monti; Aapo Hyvärinen (UAI, 2020)

A unified view for unsupervised representation learning with density ratio estimation: Maximization of mutual information, nonlinear ICA and nonlinear subspace estimation. - Hiroaki Sasaki; Takashi Takenouchi (CoRR, 2021)

Mode estimation on matrix manifolds: Convergence and robustness. - Hiroaki Sasaki; Jun-Ichiro Hirayama; Takafumi Kanamori (AISTATS, 2022)

Representation Learning for Maximization of MI, Nonlinear ICA and Nonlinear Subspaces with Robust Density Ratio Estimation. - Hiroaki Sasaki; Takashi Takenouchi (J. Mach. Learn. Res., 2022)

Graph Embedding with Outlier-Robust Ratio Estimation. - Kaito Satta; Hiroaki Sasaki (IEICE Trans. Inf. Syst., 2022)

Identifiability of a statistical model with two latent vectors: Importance of the dimensionality relation and application to graph embedding. - Hiroaki Sasaki (CoRR, 2024)