Follow
Ryo Karakida
Ryo Karakida
AIST (National Institute of Advanced Industrial Science and Technology)
Verified email at aist.go.jp - Homepage
Title
Cited by
Cited by
Year
Universal statistics of Fisher information in deep neural networks: mean field approach
R Karakida, S Akaho, S Amari
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018
802018
Information geometry connecting Wasserstein distance and Kullback–Leibler divergence via the entropy-relaxed transportation problem
S Amari, R Karakida, M Oizumi
Information Geometry 1 (1), 13-37, 2018
582018
Dynamical analysis of contrastive divergence learning: Restricted Boltzmann machines with Gaussian visible units
R Karakida, M Okada, S Amari
Neural Networks 79, 78-87, 2016
382016
Fisher information and natural gradient learning in random deep networks
S Amari, R Karakida, M Oizumi
International Conference on Artificial Intelligence and Statistics, 694-702, 2019
252019
The normalization method for alleviating pathological sharpness in wide neural networks
R Karakida, S Akaho, S Amari
Advances in Neural Information Processing Systems, 6406--6416, 2019
232019
Dynamics of learning in MLP: Natural gradient and singularity revisited
S Amari, T Ozeki, R Karakida, Y Yoshida, M Okada
Neural computation 30 (1), 1-33, 2017
232017
Pathological Spectra of the Fisher Information Metric and Its Variants in Deep Neural Networks
R Karakida, S Akaho, S Amari
Neural Computation 33 (8), 2274-2307, 2021
192021
Information geometry for regularized optimal transport and barycenters of patterns
S Amari, R Karakida, M Oizumi, M Cuturi
Neural computation 31 (5), 827-848, 2019
182019
Statistical mechanical analysis of online learning with weight normalization in single layer perceptron
Y Yoshida, R Karakida, M Okada, S Amari
Journal of the Physical Society of Japan 86 (4), 044002, 2017
152017
Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks
R Karakida, K Osawa
Advances in Neural Information Processing Systems (NeurIPS), 2020
112020
Statistical mechanical analysis of learning dynamics of two-layer perceptron with multiple output units
Y Yoshida, R Karakida, M Okada, SI Amari
Journal of Physics A: Mathematical and Theoretical 52 (18), 184002, 2019
112019
Statistical neurodynamics of deep networks: Geometry of signal spaces
S Amari, R Karakida, M Oizumi
Nonlinear Theory and Its Applications, IEICE 10 (4), 322-336, 2019
72019
Analyzing feature extraction by contrastive divergence learning in RBMs
R Karakida, M Okada, S Amari
Deep learning and representation learning workshop: NIPS, 2014
72014
Self-paced data augmentation for training neural networks
T Takase, R Karakida, H Asoh
Neurocomputing 442, 296-306, 2021
62021
Adaptive Natural Gradient Learning Algorithms for Unnormalized Statistical Models
R Karakida, M Okada, S Amari
Proceedings of International Conference on Artificial Neural Networks (ICANN …, 2016
52016
Information geometry of wasserstein divergence
R Karakida, S Amari
International Conference on Geometric Science of Information, 119-126, 2017
42017
The spectrum of Fisher information of deep networks achieving dynamical isometry
T Hayase, R Karakida
International Conference on Artificial Intelligence and Statistics, 334-342, 2021
32021
Statistical neurodynamics of deep networks I
S Amari, R Karakida, M Oizumi
Geometry of signal spaces. arXiv, 2018
22018
Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold
R Karakida, M Okada, S Amari
Proceedings of 24th European Symposium on Artificial Neural Networks …, 2016
22016
Input response of neural network model with lognormally distributed synaptic weights
Y Nagano, R Karakida, N Watanabe, A Aoyama, M Okada
Journal of the Physical Society of Japan 85 (7), 074001, 2016
12016
The system can't perform the operation now. Try again later.
Articles 1–20