Nonlinear and Noisy Extension of Independent Component Analysis: Theory and Its Application to a Pitch Sensation Model. - Shin-ichi Maeda; Wen-Jie Song; Shin Ishii (Neural Comput., 2005)

Edge-Preserving Bayesian Image Superresolution Based on Compound Markov Random Fields. - Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (ICANN (2), 2007)

Optimization of Parametric Companding Function for an Efficient Coding. - Shin-ichi Maeda; Shin Ishii (ICONIP (1), 2007)

Estimation of the Source-Filter Model Using Temporal Dynamics. - Mizuki Ihara; Shin-ichi Maeda; Shin Ishii (IJCNN, 2007)

Markov and Semi-Markov Switching of Source Appearances for Nonstationary Independent Component Analysis. - Junichiro Hirayama; Shin-ichi Maeda; Shin Ishii (IEEE Trans. Neural Networks, 2007)

A semiparametric statistical approach to model-free policy evaluation. - Tsuyoshi Ueno; Motoaki Kawanabe; Takeshi Mori; Shin-ichi Maeda; Shin Ishii (ICML, 2008)

Learning color image expansion filters. - Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (ICIP, 2009)

Superresolution from Occluded Scenes. - Wataru Fukuda; Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (ICONIP (2), 2009)

Learning of Go Board State Evaluation Function by Artificial Neural Network. - Hiroki Tomizawa; Shin-ichi Maeda; Shin Ishii (ICONIP (1), 2009)

Optimal Online Learning Procedures for Model-Free Policy Evaluation. - Tsuyoshi Ueno; Shin-ichi Maeda; Motoaki Kawanabe; Shin Ishii (ECML/PKDD (2), 2009)

Solo instrumental music analysis using the source-filter model as a sound production model considering temporal dynamics. - Mizuki Ihara; Shin-ichi Maeda; Shin Ishii (Neural Comput. Appl., 2009)

Superresolution with compound Markov random fields via the variational EM algorithm. - Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (Neural Networks, 2009)

Learning a multi-dimensional companding function for lossy source coding. - Shin-ichi Maeda; Shin Ishii (Neural Networks, 2009)

Bayesian X-ray computed tomography using material class knowledge. - Wataru Fukuda; Shin-ichi Maeda; Atsunori Kanemura; Shin Ishii (ICASSP, 2010)

Bayesian image superresolution and hidden variable modeling. - Atsunori Kanemura; Shin-ichi Maeda; Wataru Fukuda; Shin Ishii (J. Syst. Sci. Complex., 2010)

Sparse Bayesian Learning of Filters for Efficient Image Expansion. - Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (IEEE Trans. Image Process., 2010)

Motion Compensated X-ray CT Algorithm for Moving Objects. - Takumi Tanaka; Shin-ichi Maeda; Shin Ishii (ICMLA (1), 2011)

Generalized TD Learning. - Tsuyoshi Ueno; Shin-ichi Maeda; Motoaki Kawanabe; Shin Ishii (J. Mach. Learn. Res., 2011)

Control of a Free-Falling Cat by Policy-Based Reinforcement Learning. - Daichi Nakano; Shin-ichi Maeda; Shin Ishii (ICANN (2), 2012)

Asymptotic analysis of value prediction by well-specified and misspecified models. - Tsuyoshi Ueno; Shin-ichi Maeda; Shin Ishii (Neural Networks, 2012)

A Bayesian encourages dropout. - Shin-ichi Maeda (CoRR, 2014)

Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias. - Yohei Kondo; Shin-ichi Maeda; Kohei Hayashi (ACML, 2015)

Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood. - Kohei Hayashi; Shin-ichi Maeda; Ryohei Fujimaki (ICML, 2015)

Efficient Monte Carlo Image Analysis for the Location of Vascular Entity. - Henrik Skibbe; Marco Reisert; Shin-ichi Maeda; Masanori Koyama; Shigeyuki Oba; Kei Ito; Shin Ishii (IEEE Trans. Medical Imaging, 2015)

Data-Driven Probabilistic Occlusion Mask to Promote Visual Tracking. - Kourosh Meshgi; Shin-ichi Maeda; Shigeyuki Oba; Shin Ishii (CRV, 2016)

Distributional Smoothing by Virtual Adversarial Examples. - Takeru Miyato; Shin-ichi Maeda; Masanori Koyama; Ken Nakae; Shin Ishii (ICLR (Poster), 2016)

An occlusion-aware particle filter tracker to handle complex and persistent occlusions. - Kourosh Meshgi; Shin-ichi Maeda; Shigeyuki Oba; Henrik Skibbe; Yu-zhe Li; Shin Ishii (Comput. Vis. Image Underst., 2016)

Synthetic Gradient Methods with Virtual Forward-Backward Networks. - Takeru Miyato; Daisuke Okanohara; Shin-ichi Maeda; Masanori Koyama (ICLR (Workshop), 2017)

Neural Sequence Model Training via $α$-divergence Minimization. - Sotetsu Koyamada; Yuta Kikuchi; Atsunori Kanemura; Shin-ichi Maeda; Shin Ishii (CoRR, 2017)

Semi-supervised learning of hierarchical representations of molecules using neural message passing. - Hai Nguyen; Shin-ichi Maeda; Kenta Oono (CoRR, 2017)

Sparse Bayesian linear regression with latent masking variables. - Yohei Kondo; Kohei Hayashi; Shin-ichi Maeda (Neurocomputing, 2017)

CyanoBase: a large-scale update on its 20th anniversary. - Takatomo Fujisawa; Rei Narikawa; Shin-ichi Maeda; Satoru Watanabe; Yu Kanesaki; Koichi Kobayashi; Jiro Nomata; Mitsumasa Hanaoka; Mai Watanabe; Shigeki Ehira; Eiji Suzuki; Koichiro Awai; et al. (Nucleic Acids Res., 2017)

Constructing a meta-tracker using Dropout to imitate the behavior of an arbitrary black-box tracker. - Kourosh Meshgi; Shin-ichi Maeda; Shigeyuki Oba; Shin Ishii (Neural Networks, 2017)

Neural Multi-scale Image Compression. - Ken M. Nakanishi; Shin-ichi Maeda; Takeru Miyato; Daisuke Okanohara (ACCV (6), 2018)

Clipped Action Policy Gradient. - Yasuhiro Fujita 001; Shin-ichi Maeda (ICML, 2018)

BayesGrad: Explaining Predictions of Graph Convolutional Networks. - Hirotaka Akita; Kosuke Nakago; Tomoki Komatsu; Yohei Sugawara; Shin-ichi Maeda; Yukino Baba; Hisashi Kashima (ICONIP (5), 2018)

DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback. - Riku Arakawa; Sosuke Kobayashi; Yuya Unno; Yuta Tsuboi; Shin-ichi Maeda (CoRR, 2018)

Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks. - Kohei Hayashi; Taiki Yamaguchi; Yohei Sugawara; Shin-ichi Maeda (NeurIPS, 2019)

Robustness to Adversarial Perturbations in Learning from Incomplete Data. - Amir Najafi 002; Shin-ichi Maeda; Masanori Koyama; Takeru Miyato (NeurIPS, 2019)

Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks. - Katsuhiko Ishiguro; Shin-ichi Maeda; Masanori Koyama (CoRR, 2019)

Einconv: Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks. - Kohei Hayashi; Taiki Yamaguchi; Yohei Sugawara; Shin-ichi Maeda (CoRR, 2019)

Reconnaissance and Planning algorithm for constrained MDP. - Shin-ichi Maeda; Hayato Watahiki; Shintarou Okada; Masanori Koyama (CoRR, 2019)

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning. - Takeru Miyato; Shin-ichi Maeda; Masanori Koyama; Shin Ishii (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

MANGA: Method Agnostic Neural-policy Generalization and Adaptation. - Homanga Bharadhwaj; Shoichiro Yamaguchi; Shin-ichi Maeda (ICRA, 2020)

Meta Learning as Bayes Risk Minimization. - Shin-ichi Maeda; Toshiki Nakanishi; Masanori Koyama (CoRR, 2020)

Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency. - Aditya Ganeshan; Alexis Vallet; Yasunori Kudo; Shin-ichi Maeda; Tommi Kerola; Rares Ambrus; Dennis Park; Adrien Gaidon (ICCV, 2021)

Uncertainty-aware Self-supervised Target-mass Grasping of Granular Foods. - Kuniyuki Takahashi; Wilson Ko; Avinash Ummadisingu; Shin-ichi Maeda (ICRA, 2021)

Reconnaissance for Reinforcement Learning with Safety Constraints. - Shin-ichi Maeda; Hayato Watahiki; Yi Ouyang; Shintarou Okada; Masanori Koyama; Prabhat Nagarajan (ECML/PKDD (2), 2021)

A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training. - Hiroaki Mikami; Kenji Fukumizu; Shogo Murai; Shuji Suzuki; Yuta Kikuchi; Taiji Suzuki; Shin-ichi Maeda; Kohei Hayashi (CoRR, 2021)

A Scaling Law for Syn2real Transfer: How Much Is Your Pre-training Effective? - Hiroaki Mikami; Kenji Fukumizu; Shogo Murai; Shuji Suzuki; Yuta Kikuchi; Taiji Suzuki; Shin-ichi Maeda; Kohei Hayashi (ECML/PKDD (3), 2022)

F3 Hand: A Versatile Robot Hand Inspired by Human Thumb and Index Fingers. - Naoki Fukaya; Avinash Ummadisingu; Guilherme Maeda; Shin-ichi Maeda (RO-MAN, 2022)

F1 Hand: A Versatile Fixed-Finger Gripper for Delicate Teleoperation and Autonomous Grasping. - Guilherme Maeda; Naoki Fukaya; Shin-ichi Maeda (IEEE Robotics Autom. Lett., 2022)

JPEG Information Regularized Deep Image Prior for Denoising. - Tsukasa Takagi; Shinya Ishizaki; Shin-ichi Maeda (ICIP, 2023)

Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network. - Yuri Kinoshita; Kenta Oono; Kenji Fukumizu; Yuichi Yoshida; Shin-ichi Maeda (ICML, 2023)

Two-Fingered Hand with Gear-Type Synchronization Mechanism with Magnet for Improved Small and Offset Objects Grasping: F2 Hand. - Naoki Fukaya; Avinash Ummadisingu; Kuniyuki Takahashi; Guilherme Maeda; Shin-ichi Maeda (IROS, 2023)

Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics. - Kenta Oono; Nontawat Charoenphakdee; Kotatsu Bito; Zhengyan Gao; Yoshiaki Ota; Shoichiro Yamaguchi; Yohei Sugawara; Shin-ichi Maeda; Kunihiko Miyoshi; Yuki Saito; Koki Tsuda; Hiroshi Maruyama; et al. (CoRR, 2023)

Helical Three Dimensional Reconstruction Using Bayesian Optimization for Cryogenic Electron Microscopy. - Masataka Ohashi; Shin-ichi Maeda; Chikara Sato (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Four-Axis Adaptive Fingers Hand for Object Insertion: FAAF Hand. - Naoki Fukaya; Koki Yamane; Shimpei Masuda; Avinash Ummadisingu; Shin-ichi Maeda; Kuniyuki Takahashi (IROS, 2024)

Deep Bayesian Filter for Bayes-faithful Data Assimilation. - Yuta Tarumi; Keisuke Fukuda; Shin-ichi Maeda (CoRR, 2024)

Segmentation with Noisy Labels via Spatially Correlated Distributions. - Ryu Tadokoro; Tsukasa Takagi; Shin-ichi Maeda (CoRR, 2025)