From the 1 of 11 linked papers with an AI index.
11 papers
Autocorrelation effects in a stochastic-process model for solving two-armed bandit problems
Tomoki Yamagami, Mikio Hasegawa, Takatomo Mihana +2
The paper studies how autocorrelation in photonic chaotic signals influences the performance of a stochastic-process model for solving two-armed bandit problems, showing that negat…
EDoF-NeRF: extended depth-of-field neural radiance fields using a coded aperture camera
Yoshiyuki Shirasaki, Ryoichi Horisaki
We propose a method for extending the depth-of-field (DoF) to construct high-fidelity neural radiance fields (NeRF) -- an emerging technique for rendering photorealistic novel view…
Time-multiplexed layer reuse for physical neural networks
Kohei Tsuchiyama, Andre Roehm, Takatomo Mihana +1
Physical neural networks (PNNs) are promising candidates for next-generation computing, but existing demonstrations remain several orders of magnitude smaller than modern digital n…
Cathodoluminescence Wavefront Retrieval
Izzah Machfuudzoh, Ryoichi Horisaki, Takumi Sannomiya
Free-electron-based nanoscopy enables the study of optical excitations in materials with deep-subwavelength spatial resolution, with cathodoluminescence (CL) being one of the resul…
Quantum spatial best-arm identification via quantum walks
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana +3
Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to the multi-armed bandit (MAB) problem ha…
Compressive multi-beam scanning transmission electron microscopy
Akira Yasuhara, Takumi Sannomiya, Ryoichi Horisaki
We demonstrate a multi-beam scanning transmission electron microscopy (STEM) imaging that integrates down-sampling with super-resolution image reconstruction via a compressive sens…