1 code implementation • 21 Oct 2022 • Kohei Ichikawa, Kunihiko Kaneko
In performing Bayesian inference, the prior distribution must be shaped by sampling noisy external inputs.
no code implementations • 29 Jun 2021 • Fadi Boutros, Naser Damer, Jan Niklas Kolf, Kiran Raja, Florian Kirchbuchner, Raghavendra Ramachandra, Arjan Kuijper, Pengcheng Fang, Chao Zhang, Fei Wang, David Montero, Naiara Aginako, Basilio Sierra, Marcos Nieto, Mustafa Ekrem Erakin, Ugur Demir, Hazim Kemal, Ekenel, Asaki Kataoka, Kohei Ichikawa, Shizuma Kubo, Jie Zhang, Mingjie He, Dan Han, Shiguang Shan, Klemen Grm, Vitomir Štruc, Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Pedro C. Neto, Ana F. Sequeira, Joao Ribeiro Pinto, Mohsen Saffari, Jaime S. Cardoso
These teams successfully submitted 18 valid solutions.
1 code implementation • 10 Jun 2021 • Kohei Ichikawa, Asaki Kataoka
As a result, it was found that sampling in RNN is performed by a mechanism that efficiently utilizes the properties of dynamical systems, unlike FFNN.
no code implementations • 8 Feb 2021 • Ryan W. Pfeifle, Claudio Ricci, Peter G. Boorman, Marko Stalevski, Daniel Asmus, Benny Trakhtenbrot, Michael J. Koss, Daniel Stern, Federica Ricci, Shobita Satyapal, Kohei Ichikawa, David J. Rosario, Turgay Caglar, Ezequiel Treister, Meredith Powell, Kyuseok Oh, C. Megan Urry, Fiona Harrison
In this study, we use the SWIFT/BAT AGN sample, which has received extensive multiwavelength follow-up analysis as a result of the BAT AGN Spectroscopic Survey (BASS), to develop a diagnostic for nuclear obscuration by examining the relationship between the line-of-sight column densities ($N_{\rm{H}}$), the 2-10 keV-to-$12\,\rm{\mu m}$ luminosity ratio, and WISE mid-infrared colors.
Astrophysics of Galaxies
1 code implementation • 2 Dec 2020 • Wassapon Watanakeesuntorn, Keichi Takahashi, Kohei Ichikawa, Joseph Park, George Sugihara, Ryousei Takano, Jason Haga, Gerald M. Pao
Empirical Dynamic Modeling (EDM) is a nonlinear time series causal inference framework.
no code implementations • 29 Oct 2020 • Kohei Ichikawa, Kunihiko Kaneko
By training recurrent neural networks to short-term memory tasks and analyzing the dynamics, the characteristics of the short-term memory mechanism were obtained in which the input information was encoded in the amplitude of transient oscillations, rather than the stationary neural activities.