Shinichi Nakajima

Berliner Institut für Sozialforschung — Germany

Computer Science · Physical Sciences

21h-index3.3kcitations269works1.92yr avg
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Research Topics

Bayesian Methods and Mixture Models(25), Blind Source Separation Techniques(22), Face and Expression Recognition(21), Sparse and Compressive Sensing Techniques(18), Advanced Manufacturing and Logistics Optimization(18)

Publications269 total

Towards Symbolic XAI – Explanation Through Human Understandable Logical Relationships Between Features
2025
Uncovering the Structure of Explanation Quality with Spectral Analysis
Communications in computer and information science·2025Open Access
Enhancing Brain Source Reconstruction by Initializing 3-D Neural Networks With Physical Inverse Solutions
IEEE Transactions on Medical Imaging·2025· 1 citedOpen Access
Data augmentation for forecasting industrial aging processes via conditional multimodal generative time-series models
Computers & Chemical Engineering·2025· 1 citedOpen Access
Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects
Physical Review Letters·2025· 3 cited
Multilevel Generative Samplers for Investigating Critical Phenomena
arXiv (Cornell University)·2025· 1 citedOpen Access
Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models
arXiv (Cornell University)·2025Open Access
Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers
arXiv (Cornell University)·2025Open Access
Adaptive Observation Cost Control for Variational Quantum Eigensolvers
arXiv (Cornell University)·2025Open Access
Improvement of Heatbath Algorithm in LFT using Generative models
2025Open Access
Towards symbolic XAI — explanation through human understandable logical relationships between features
Information Fusion·2025· 6 citedOpen Access
Self-Supervised Autoencoders for Visual Anomaly Detection
Mathematics·2024· 8 citedOpen Access
Enhancing Brain Source Reconstruction through Physics-Informed 3D Neural Networks
arXiv (Cornell University)·2024· 3 citedOpen Access
Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects
arXiv (Cornell University)·2024· 1 citedOpen Access
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
arXiv (Cornell University)·2024· 2 citedOpen Access
Molecular relaxation by reverse diffusion with time step prediction
Machine Learning Science and Technology·2024· 5 citedOpen Access
Machine learning-assisted equivalent circuit identification for dielectric spectroscopy of polymers
Electrochimica Acta·2024· 6 citedOpen Access
Federated Learning over Connected Modes
arXiv (Cornell University)·2024Open Access
Generative Fractional Diffusion Models
2024
Physics-Informed Bayesian Optimization of Variational Quantum Circuits
arXiv (Cornell University)·2024· 3 citedOpen Access
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Frequent Co-authors

Masashi Sugiyama(12), Klaus‐Robert Müller(11), Wojciech Samek(7), Marius Kloft(6), Motoaki Kawanabe(5), S. Derin Babacan(5), Kim A. Nicoli(5), Pan Kessel(5), Christopher J. Anders(3), Tobias Hartung(3), Karl Jansen(3), Ryota Tomioka(3), Kirill Bykov(3), Marina Höhne(3), Alexander Binder(3), Paul von Bünau(2), Tsuyoshi Idé(2), Jun Sese(2), Thomas Schnake(2), Oliver Eberle(2)