no code implementations • 6 Dec 2023 • Daiki Sekizawa, Sosuke Ito, Masafumi Oizumi
Our decomposition enables us to calculate the contribution to the housekeeping entropy production rate from oscillatory modes, as well as the spatial distribution of the contributions.
no code implementations • 8 Aug 2023 • Genji Kawakita, Ariel Zeleznikow-Johnston, Naotsugu Tsuchiya, Masafumi Oizumi
These results contribute to our understanding of the ability of LLMs to accurately infer human perception, and highlight the potential of unsupervised alignment methods to reveal detailed structural equivalence or differences that cannot be detected by simple correlation analysis.
no code implementations • 22 Aug 2018 • Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi
The manifold of input signals is embedded in a higher dimensional manifold of the next layer as a curved submanifold, provided the number of neurons is larger than that of inputs.
no code implementations • 22 Aug 2018 • Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi
The natural gradient method uses the steepest descent direction in a Riemannian manifold, so it is effective in learning, avoiding plateaus.
no code implementations • 19 Dec 2017 • Jun Kitazono, Ryota Kanai, Masafumi Oizumi
In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of $\Phi$ by evaluating the accuracy of the algorithm in simulated data and real neural data.
no code implementations • NeurIPS 2008 • Masafumi Oizumi, Toshiyuki Ishii, Kazuya Ishibashi, Toshihiko Hosoya, Masato Okada
Then, we compute how much information is lost when information is decoded using the simplified models, i. e., ``mismatched decoders''.
