| 2025 | ICLR | Multilevel Generative Samplers for Investigating Critical Phenomena. | Ankur Singha, Elia Cellini, Kim Andrea Nicoli, Karl Jansen, Stefan Khn, Shinichi Nakajima |
| 2024 | ICML | 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 Khn, Shinichi Nakajima |
| 2023 | ICML | Relevant Walk Search for Explaining Graph Neural Networks. | Ping Xiong, Thomas Schnake, Michael Gastegger, Grgoire Montavon, Klaus-Robert Mller, Shinichi Nakajima |
| 2022 | AAAI | NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights. | Kirill Bykov, Anna Hedstrm, Shinichi Nakajima, Marina M.-C. Hhne |
| 2022 | ICML | Path-Gradient Estimators for Continuous Normalizing Flows. | Lorenz Vaitl, Kim Andrea Nicoli, Shinichi Nakajima, Pan Kessel |
| 2022 | ICML | Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. | Ping Xiong, Thomas Schnake, Grgoire Montavon, Klaus-Robert Mller, Shinichi Nakajima |
| 2020 | AAAI | Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. | Vignesh Srinivasan, Klaus-Robert Mller, Wojciech Samek, Shinichi Nakajima |
| 2020 | IJCNN | Towards Best Practice in Explaining Neural Network Decisions with LRP. | Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin |
| 2019 | AISTATS | Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. | Alexander Bauer, Shinichi Nakajima, Nico Grnitz, Klaus-Robert Mller |
| 2017 | ICML | Minimizing Trust Leaks for Robust Sybil Detection. | Jnos Hner, Shinichi Nakajima, Alexander Bauer, Klaus-Robert Mller, Nico Grnitz |
| 2016 | UAI | Separating Sparse Signals from Correlated Noise in Binary Classification. | Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft |
| 2014 | AISTATS | Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes? | Shinichi Nakajima, Masashi Sugiyama |
| 2011 | ICML | On Bayesian PCA: Automatic Dimensionality Selection and Analytic Solution. | Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan |
| 2010 | ICML | Implicit Regularization in Variational Bayesian Matrix Factorization. | Shinichi Nakajima, Masashi Sugiyama |
| 2009 | ICML | Multi-class image segmentation using conditional random fields and global classification. | Nils Plath, Marc Toussaint, Shinichi Nakajima |
| 2009 | PAKDD | Analysis of Variational Bayesian Matrix Factorization. | Shinichi Nakajima, Masashi Sugiyama |
| 2008 | PAKDD | Semi-Supervised Local Fisher Discriminant Analysis for Dimensionality Reduction. | Masashi Sugiyama, Tsuyoshi Id, Shinichi Nakajima, Jun Sese |
| 2007 | ICANN | Generalization Error of Automatic Relevance Determination. | Shinichi Nakajima, Sumio Watanabe |
| 2006 | ICANN | Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem. | Shinichi Nakajima, Sumio Watanabe |
| 2006 | ICONIP | Localized Bayes Estimation for Non-identifiable Models. | Shingo Takamatsu, Shinichi Nakajima, Sumio Watanabe |
| 2005 | IJCAI | Generalization Error of Linear Neural Networks in an Empirical Bayes Approach. | Shinichi Nakajima, Sumio Watanabe |