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- The University of TokyoJP116 papers
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- The University of OsakaJP32 papers
- Tokyo Institute of TechnologyJP27 papers
- Japan Science and Technology AgencyJP25 papers
- National Institute for Materials ScienceJP25 papers
- University of TsukubaJP25 papers
- Japan Atomic Energy AgencyJP21 papers
- Kyushu UniversityJP18 papers
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439 papers
Interpretation of the binned SNe Ia Master Sample data via a scalar quintessence component: phantom transition?
Giovanni Montani, Iolanda Navone, Maria Giovanna Dainotti +1
We study a modified cosmological scenario for the late Universe, involving an evolutionary dark energy model associated with the dynamics of a self-interacting scalar field in a po…
Dynamical Regimes of Discrete Diffusion Models
Tomoei Takahashi, Takashi Takahashi, Yoshiyuki Kabashima
Diffusion models generate high-dimensional data such as images by learning a process that gradually removes noise from corrupted data. Recent studies have shown that the backward d…
SIRUP: A diffusion-based virtual upmixer of steering vectors for highly-directive spatialization with first-order ambisonics
Emilio Picard, Diego Di Carlo, Aditya Arie Nugraha +2
This paper presents virtual upmixing of steering vectors captured by a fewer-channel spherical microphone array. This challenge has conventionally been addressed by recovering the…
Thermodynamic Limits of Physical Intelligence
Koichi Takahashi, Yusuke Hayashi
Modern AI systems achieve remarkable capabilities at the cost of substantial energy consumption. To connect intelligence to physical efficiency, we propose two complementary bits-p…
An Efficient Algorithm for Thresholding Monte Carlo Tree Search
Shoma Nameki, Atsuyoshi Nakamura, Junpei Komiyama +1
We introduce the Thresholding Monte Carlo Tree Search problem, in which, given a tree and a threshold , a player must answer whether the root node value of $\mathc…
Variational Gaussian Approximation in Replica Analysis of Parametric Models
Takashi Takahashi
We revisit the replica method for analyzing inference and learning in parametric models, considering situations where the data-generating distribution is unknown or analytically in…