| Neural network with unbounded activation functions is universal approximator S Sonoda, N Murata Applied and Computational Harmonic Analysis 43 (2), 233-268, 2015 | 260 | 2015 |
| Double Continuum Limit of Deep Neural Networks S Sonoda, N Murata ICML 2017 Workshop on Principled Approaches to Deep Learning, 1-5, 2017 | 37 | 2017 |
| Transport Analysis of Infinitely Deep Neural Network S Sonoda, N Murata Journal of Machine Learning Research, 2016 | 37* | 2016 |
| A statistical model for predicting the liquid steel temperature in ladle and tundish by bootstrap filter S Sonoda, N Murata, H Hino, H Kitada, M Kano ISIJ international 52 (6), 1086-1091, 2012 | 25 | 2012 |
| Neural network with unbounded activations is universal approximator S Sonoda, N Murata CoRR, abs/1505.03654, 2015 | 14 | 2015 |
| Sampling hidden parameters from oracle distribution S Sonoda, N Murata International Conference on Artificial Neural Networks, 539-546, 2014 | 12 | 2014 |
| Differentiable multiple shooting layers S Massaroli, M Poli, S Sonoda, T Suzuki, J Park, A Yamashita, H Asama Advances in Neural Information Processing Systems 34, 16532-16544, 2021 | 6 | 2021 |
| The global optimum of shallow neural network is attained by ridgelet transform S Sonoda, I Ishikawa, M Ikeda, K Hagihara, Y Sawano, T Matsubara, ... arXiv preprint arXiv:1805.07517v3, 2019 | 6 | 2019 |
| Learning with optimized random features: Exponential speedup by quantum machine learning without sparsity and low-rank assumptions H Yamasaki, S Subramanian, S Sonoda, M Koashi Advances in Neural Information Processing Systems 33, 13674-13687, 2020 | 5 | 2020 |
| Transportation analysis of denoising autoencoders: a novel method for analyzing deep neural networks S Sonoda, N Murata NIPS Workshop on Optimal Transport & Machine Learning, 2017 | 5 | 2017 |
| Nonparametric weight initialization of neural networks via integral representation S Sonoda, N Murata arXiv preprint arXiv:1312.6461, 2013 | 5 | 2013 |
| EEG dipole source localization with information criteria for multiple particle filters S Sonoda, K Nakamura, Y Kaneda, H Hino, S Akaho, N Murata, ... Neural networks 108, 68-82, 2018 | 4 | 2018 |
| Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum S Sonoda, I Ishikawa, M Ikeda International Conference on Artificial Intelligence and Statistics, 2674-2682, 2021 | 3 | 2021 |
| Fast quantum algorithm for learning with optimized random features H Yamasaki, S Subramanian, S Sonoda, M Koashi Advances in Neural Information Processing Systems, 1-10, 2020 | 3 | 2020 |
| Sensitivity analysis for controlling molten steel temperature in tundish N Murata, S Sonoda, H Hino, H Kitada, M Kano IFAC Proceedings Volumes 45 (23), 270-271, 2012 | 3 | 2012 |
| On the approximation lower bound for neural nets with random weights S Sonoda, M Li, F Cao, C Huang, YG Wang arXiv preprint arXiv:2008.08427, 2020 | 2 | 2020 |
| Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis S Sonoda, I Ishikawa, M Ikeda arXiv preprint arXiv:2203.01631, 2022 | 1 | 2022 |
| Exponential error convergence in data classification with optimized random features: Acceleration by quantum machine learning H Yamasaki, S Sonoda arXiv preprint arXiv:2106.09028, 2021 | 1 | 2021 |
| Fast Approximation and Estimation Bounds of Kernel Quadrature for Infinitely Wide Models S Sonoda arXiv preprint arXiv:1902.00648, 2019 | 1 | 2019 |
| 深層ニューラルネットの積分表現理論 園田翔 博士論文, 早稲田大学, 2016 | 1 | 2016 |
Noboru MurataWaseda UniversityVerified email at eb.waseda.ac.jp
