Generalization Error of Linear Neural Networks in an Empirical Bayes Approach. - Shinichi Nakajima; Sumio Watanabe (IJCAI, 2005)

Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem. - Shinichi Nakajima; Sumio Watanabe (ICANN (2), 2006)

Localized Bayes Estimation for Non-identifiable Models. - Shingo Takamatsu; Shinichi Nakajima; Sumio Watanabe (ICONIP (1), 2006)

Generalization Performance of Subspace Bayes Approach in Linear Neural Networks. - Shinichi Nakajima; Sumio Watanabe (IEICE Trans. Inf. Syst., 2006)

Generalization Error of Automatic Relevance Determination. - Shinichi Nakajima; Sumio Watanabe (ICANN (1), 2007)

Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation. - Masashi Sugiyama; Shinichi Nakajima; Hisashi Kashima; Paul von Bünau; Motoaki Kawanabe (NIPS, 2007)

Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance. - Shinichi Nakajima; Sumio Watanabe (Neural Comput., 2007)

Pool-Based Agnostic Experiment Design in Linear Regression. - Masashi Sugiyama; Shinichi Nakajima (ECML/PKDD (2), 2008)

A procedure of adaptive kernel combination with kernel-target alignment for object classification. - Motoaki Kawanabe; Shinichi Nakajima; Alexander Binder (CIVR, 2009)

Multi-class image segmentation using conditional random fields and global classification. - Nils Plath; Marc Toussaint; Shinichi Nakajima (ICML, 2009)

Analysis of Variational Bayesian Matrix Factorization. - Shinichi Nakajima; Masashi Sugiyama (PAKDD, 2009)

Feature Selection for Density Level-Sets. - Marius Kloft; Shinichi Nakajima; Ulf Brefeld (ECML/PKDD (1), 2009)

Pool-based active learning in approximate linear regression. - Masashi Sugiyama; Shinichi Nakajima (Mach. Learn., 2009)

Implicit Regularization in Variational Bayesian Matrix Factorization. - Shinichi Nakajima; Masashi Sugiyama (ICML, 2010)

Global Analytic Solution for Variational Bayesian Matrix Factorization. - Shinichi Nakajima; Masashi Sugiyama; Ryota Tomioka (NIPS, 2010)

Nikon Multimedia Event Detection System. - Takeshi Matsuo; Shinichi Nakajima (TRECVID, 2010)

Semi-supervised local Fisher discriminant analysis for dimensionality reduction. - Masashi Sugiyama; Tsuyoshi Idé; Shinichi Nakajima; Jun Sese (Mach. Learn., 2010)

On Bayesian PCA: Automatic Dimensionality Selection and Analytic Solution. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan (ICML, 2011)

Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan (NIPS, 2011)

Attribute-Based MED System with Word Histograms. - Takeshi Matsuo; Shinichi Nakajima (TRECVID, 2011)

Insights from Classifying Visual Concepts with Multiple Kernel Learning - Alexander Binder; Shinichi Nakajima; Marius Kloft; Christina Müller; Wojciech Samek; Ulf Brefeld; Klaus-Robert Müller; Motoaki Kawanabe (CoRR, 2011)

Theoretical Analysis of Bayesian Matrix Factorization. - Shinichi Nakajima; Masashi Sugiyama (J. Mach. Learn. Res., 2011)

Probabilistic Low-Rank Subspace Clustering. - S. Derin Babacan; Shinichi Nakajima; Minh N. Do (NIPS, 2012)

Perfect Dimensionality Recovery by Variational Bayesian PCA. - Shinichi Nakajima; Ryota Tomioka; Masashi Sugiyama; S. Derin Babacan (NIPS, 2012)

Sparse Additive Matrix Factorization for Robust PCA and Its Generalization. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan (ACML, 2012)

Light field acquisition from blurred observations using a programmable coded aperture camera. - Pablo Ruiz 002; Javier Mateos; María C. Cárdenas; Shinichi Nakajima; Rafael Molina 001; Aggelos K. Katsaggelos (EUSIPCO, 2013)

Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering. - Shinichi Nakajima; Akiko Takeda; S. Derin Babacan; Masashi Sugiyama; Ichiro Takeuchi (NIPS, 2013)

Parametric Task Learning. - Ichiro Takeuchi; Tatsuya Hongo; Masashi Sugiyama; Shinichi Nakajima (NIPS, 2013)

Global analytic solution of fully-observed variational Bayesian matrix factorization. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan; Ryota Tomioka (J. Mach. Learn. Res., 2013)

Variational Bayesian sparse additive matrix factorization. - Shinichi Nakajima; Masashi Sugiyama; S. Derin Babacan (Mach. Learn., 2013)

Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes? - Shinichi Nakajima; Masashi Sugiyama (AISTATS, 2014)

Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP. - Shinichi Nakajima; Issei Sato; Masashi Sugiyama; Kazuho Watanabe; Hiroko Kobayashi (NIPS, 2014)

Bayesian Group-Sparse Modeling and Variational Inference. - S. Derin Babacan; Shinichi Nakajima; Minh N. Do (IEEE Trans. Signal Process., 2014)

Sparse Estimation in a Correlated Probit Model. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; John P. Cunningham; Christoph Lippert; Marius Kloft (CoRR, 2015)

Condition for perfect dimensionality recovery by variational Bayesian PCA. - Shinichi Nakajima; Ryota Tomioka; Masashi Sugiyama; S. Derin Babacan (J. Mach. Learn. Res., 2015)

Separating Sparse Signals from Correlated Noise in Binary Classification. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; Christoph Lippert; Marius Kloft (CFA@UAI, 2016)

SynsetRank: Degree-adjusted Random Walk for Relation Identification. - Shinichi Nakajima; Sebastian Krause; Dirk Weissenborn; Sven Schmeier; Nico Görnitz; Feiyu Xu (CoRR, 2016)

Sharing Hash Codes for Multiple Purposes. - Wikor Pronobis; Danny Panknin; Johannes Kirschnick; Vignesh Srinivasan; Wojciech Samek; Volker Markl; Manohar Kaul; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2016)

Variational Robust Subspace Clustering with Mean Update Algorithm. - Sergej Dogadov; Andrés R. Masegosa; Shinichi Nakajima (ICCV Workshops, 2017)

Minimizing Trust Leaks for Robust Sybil Detection. - János Höner; Shinichi Nakajima; Alexander Bauer 001; Klaus-Robert Müller; Nico Görnitz (ICML, 2017)

Porosity estimation by semi-supervised learning with sparsely available labeled samples. - Luiz Alberto Lima; Nico Görnitz; Luiz Eduardo Varella; Marley M. B. R. Vellasco; Klaus-Robert Müller; Shinichi Nakajima (Comput. Geosci., 2017)

Sparse probit linear mixed model. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; John P. Cunningham; Christoph Lippert; Marius Kloft (Mach. Learn., 2017)

Efficient Exact Inference With Loss Augmented Objective in Structured Learning. - Alexander Bauer 001; Shinichi Nakajima; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2017)

Counterstrike: Defending Deep Learning Architectures Against Adversarial Samples by Langevin Dynamics with Supervised Denoising Autoencoder. - Vignesh Srinivasan; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (CoRR, 2018)

Tight Bound of Incremental Cover Trees for Dynamic Diversification. - Hannah Marienwald; Wikor Pronobis; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2018)

Unsupervised Detection and Explanation of Latent-class Contextual Anomalies. - Jacob R. Kauffmann; Grégoire Montavon; Luiz Alberto Lima; Shinichi Nakajima; Klaus-Robert Müller; Nico Görnitz (CoRR, 2018)

Wasserstein Stationary Subspace Analysis. - Stephan Kaltenstadler; Shinichi Nakajima; Klaus-Robert Müller; Wojciech Samek (IEEE J. Sel. Top. Signal Process., 2018)

Support Vector Data Descriptions and k-Means Clustering: One Class? - Nico Görnitz; Luiz Alberto Lima; Klaus-Robert Müller; Marius Kloft; Shinichi Nakajima (IEEE Trans. Neural Networks Learn. Syst., 2018)

Transductive Regression for Data With Latent Dependence Structure. - Nico Görnitz; Luiz Alberto Lima; Luiz Eduardo Varella; Klaus-Robert Müller; Shinichi Nakajima (IEEE Trans. Neural Networks Learn. Syst., 2018)

Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. - Alexander Bauer 001; Shinichi Nakajima; Nico Görnitz; Klaus-Robert Müller (AISTATS, 2019)

Black-Box Decision based Adversarial Attack with Symmetric α-stable Distribution. - Vignesh Srinivasan; Ercan E. Kuruoglu; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (EUSIPCO, 2019)

Local Bandwidth Estimation via Mixture of Gaussian Processes. - Danny Panknin; Shinichi Nakajima; Thanh Binh Bui; Klaus-Robert Müller (CoRR, 2019)

Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling. - Kim Nicoli; Pan Kessel; Nils Strodthoff; Wojciech Samek; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2019)

Asymptotically Unbiased Generative Neural Sampling. - Kim A. Nicoli; Shinichi Nakajima; Nils Strodthoff; Wojciech Samek; Klaus-Robert Müller; Pan Kessel (CoRR, 2019)

Worst-Case Polynomial-Time Exact MAP Inference on Discrete Models with Global Dependencies. - Alexander Bauer 001; Shinichi Nakajima (CoRR, 2019)

Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (AAAI, 2020)

Accuracy vs. Cost Trade-off for Machine Learning Based QoE Estimation in 5G Networks. - Susanna Schwarzmann; Clarissa Cassales Marquezan; Riccardo Trivisonno; Shinichi Nakajima; Thomas Zinner (ICC, 2020)

Towards Best Practice in Explaining Neural Network Decisions with LRP. - Maximilian Kohlbrenner; Alexander Bauer 001; Shinichi Nakajima; Alexander Binder; Wojciech Samek; Sebastian Lapuschkin (IJCNN, 2020)

Automatic Identification of Types of Alterations in Historical Manuscripts. - David Lassner; Anne Baillot; Sergej Dogadov; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2020)

XAI for Graphs: Explaining Graph Neural Network Predictions by Identifying Relevant Walks. - Thomas Schnake; Oliver Eberle; Jonas Lederer; Shinichi Nakajima; Kristof T. Schütt; Klaus-Robert Müller; Grégoire Montavon (CoRR, 2020)

How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks. - Kirill Bykov; Marina M.-C. Höhne; Klaus-Robert Müller; Shinichi Nakajima; Marius Kloft (CoRR, 2020)

On Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models. - Kim A. Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima; Paolo Stornati (CoRR, 2020)

Langevin Cooling for Domain Translation. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (CoRR, 2020)

Optimizing for Measure of Performance in Max-Margin Parsing. - Alexander Bauer 001; Shinichi Nakajima; Nico Görnitz; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2020)

Optimal Sampling Density for Nonparametric Regression. - Danny Panknin; Shinichi Nakajima; Klaus-Robert Müller (CoRR, 2021)

Explaining Bayesian Neural Networks. - Kirill Bykov; Marina M.-C. Höhne; Adelaida Creosteanu; Klaus-Robert Müller; Frederick Klauschen; Shinichi Nakajima; Marius Kloft (CoRR, 2021)

Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse. - Kim A. Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima; Paolo Stornati (CoRR, 2021)

Robustifying models against adversarial attacks by Langevin dynamics. - Vignesh Srinivasan; Csaba Rohrer; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (Neural Networks, 2021)

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights. - Kirill Bykov; Anna Hedström; Shinichi Nakajima; Marina M.-C. Höhne (AAAI, 2022)

Path-Gradient Estimators for Continuous Normalizing Flows. - Lorenz Vaitl; Kim Andrea Nicoli; Shinichi Nakajima; Pan Kessel (ICML, 2022)

Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. - Ping Xiong 002; Thomas Schnake; Grégoire Montavon; Klaus-Robert Müller; Shinichi Nakajima (ICML, 2022)

Mixture-of-experts VAEs can disregard variation in surjective multimodal data. - Jannik Wolff; Tassilo Klein; Moin Nabi; Rahul G. Krishnan; Shinichi Nakajima (CoRR, 2022)

Higher-Order Explanations of Graph Neural Networks via Relevant Walks. - Thomas Schnake; Oliver Eberle; Jonas Lederer; Shinichi Nakajima; Kristof T. Schütt; Klaus-Robert Müller; Grégoire Montavon (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

ML-Based QoE Estimation in 5G Networks Using Different Regression Techniques. - Susanna Schwarzmann; Clarissa Cassales Marquezan; Riccardo Trivisonno; Shinichi Nakajima; Vincent Barriac; Thomas Zinner (IEEE Trans. Netw. Serv. Manag., 2022)

Gradients should stay on path: better estimators of the reverse- and forward KL divergence for normalizing flows. - Lorenz Vaitl; Kim A. Nicoli; Shinichi Nakajima; Pan Kessel (Mach. Learn. Sci. Technol., 2022)

Relevant Walk Search for Explaining Graph Neural Networks. - Ping Xiong 002; Thomas Schnake; Michael Gastegger; Grégoire Montavon; Klaus-Robert Müller; Shinichi Nakajima (ICML, 2023)

Labeling Neural Representations with Inverse Recognition. - Kirill Bykov; Laura Kopf; Shinichi Nakajima; Marius Kloft; Marina M.-C. Höhne (NeurIPS, 2023)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits. - Kim Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Stefan Kühn; Klaus-Robert Müller; Paolo Stornati; Pan Kessel; Shinichi Nakajima (NeurIPS, 2023)

Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories. - Kim A. Nicoli; Christopher J. Anders; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima (CoRR, 2023)

Generative Fractional Diffusion Models. - Gabriel Nobis; Marco Aversa; Maximilian Springenberg; Michael Detzel; Stefano Ermon; Shinichi Nakajima; Roderick Murray-Smith; Sebastian Lapuschkin; Christoph Knochenhauer; Luis Oala; Wojciech Samek (CoRR, 2023)

Domain-Specific Word Embeddings with Structure Prediction. - David Lassner; Stephanie Brandl; Anne Baillot; Shinichi Nakajima (Trans. Assoc. Comput. Linguistics, 2023)

Visualizing the Diversity of Representations Learned by Bayesian Neural Networks. - Dennis Grinwald; Kirill Bykov; Shinichi Nakajima; Marina M.-C. Höhne (Trans. Mach. Learn. Res., 2023)

Local Function Complexity for Active Learning via Mixture of Gaussian Processes. - Danny Panknin; Stefan Chmiela; Klaus-Robert Müller; Shinichi Nakajima (Trans. Mach. Learn. Res., 2023)

Langevin Cooling for Unsupervised Domain Translation. - Vignesh Srinivasan; Klaus-Robert Müller; Wojciech Samek; Shinichi Nakajima (IEEE Trans. Neural Networks Learn. Syst., 2023)

Adaptive Observation Cost Control for Variational Quantum Eigensolvers. - Christopher J. Anders; Kim Andrea Nicoli; Bingting Wu; Naima Elosegui; Samuele Pedrielli; Lena Funcke; Karl Jansen; Stefan Kühn; Shinichi Nakajima (ICML, 2024)

Federated Learning over Connected Modes. - Dennis Grinwald; Philipp Wiesner; Shinichi Nakajima (NeurIPS, 2024)

Generative Fractional Diffusion Models. - Gabriel Nobis; Maximilian Springenberg; Marco Aversa; Michael Detzel; Rembert Daems; Roderick Murray-Smith; Shinichi Nakajima; Sebastian Lapuschkin; Stefano Ermon; Tolga Birdal; Manfred Opper; Christoph Knochenhauer; et al. (NeurIPS, 2024)

Solution Simplex Clustering for Heterogeneous Federated Learning. - Dennis Grinwald; Philipp Wiesner; Shinichi Nakajima (CoRR, 2024)

Flow-based Sampling for Entanglement Entropy and the Machine Learning of Defects. - Andrea Bulgarelli; Elia Cellini; Karl Jansen; Stefan Kühn; Alessandro Nada; Shinichi Nakajima; Kim A. Nicoli; Marco Panero (CoRR, 2024)

Enhancing Brain Source Reconstruction through Physics-Informed 3D Neural Networks. - Marco Morik; Ali Hashemi 002; Klaus-Robert Müller; Stefan Haufe; Shinichi Nakajima (CoRR, 2024)

Molecular relaxation by reverse diffusion with time step prediction. - Khaled Kahouli; Stefaan Simon Pierre Hessmann; Klaus-Robert Müller; Shinichi Nakajima; Stefan Gugler; Niklas W. A. Gebauer (Mach. Learn. Sci. Technol., 2024)

MoreRed: Molecular Relaxation by Reverse Diffusion with Time Step Prediction. - Khaled Kahouli; Stefaan Simon Pierre Hessmann; Klaus-Robert Müller; Shinichi Nakajima; Stefan Gugler; Niklas W. A. Gebauer (Zenodo, 2024)

Multilevel Generative Samplers for Investigating Critical Phenomena. - Ankur Singha; Elia Cellini; Kim Andrea Nicoli; Karl Jansen; Stefan Kühn; Shinichi Nakajima (ICLR, 2025)

Data augmentation for forecasting industrial aging processes via conditional multimodal generative time-series models. - Mihail Bogojeski; Nataliya Yakut; Sasho Nedelkoski; Shinichi Nakajima; Klaus-Robert Müller (Comput. Chem. Eng., 2025)

Towards symbolic XAI - explanation through human understandable logical relationships between features. - Thomas Schnake; Farnoush Rezaei Jafari; Jonas Lederer; Ping Xiong 002; Shinichi Nakajima; Stefan Gugler; Grégoire Montavon; Klaus-Robert Müller (Inf. Fusion, 2025)

Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers. - Samuele Pedrielli; Christopher J. Anders; Lena Funcke; Karl Jansen; Kim A. Nicoli; Shinichi Nakajima (CoRR, 2025)

Enhancing Diffusion Models Efficiency by Disentangling Total-Variance and Signal-to-Noise Ratio. - Khaled Kahouli; Winfried Ripken; Stefan Gugler; Oliver T. Unke; Klaus-Robert Müller; Shinichi Nakajima (CoRR, 2025)

Uncovering the Structure of Explanation Quality with Spectral Analysis. - Johannes Maeß; Grégoire Montavon; Shinichi Nakajima; Klaus-Robert Müller; Thomas Schnake (CoRR, 2025)