Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Isomura, Takuya"'
Autor:
Isomura, Takuya
Characterising the intelligence of biological organisms is challenging. This work considers intelligent algorithms developed evolutionarily within neural systems. Mathematical analyses unveil a natural equivalence between canonical neural networks, v
Externí odkaz:
http://arxiv.org/abs/2409.04928
Given the rapid advancement of artificial intelligence, understanding the foundations of intelligent behaviour is increasingly important. Active inference, regarded as a general theory of behaviour, offers a principled approach to probing the basis o
Externí odkaz:
http://arxiv.org/abs/2403.12417
Autor:
Friston, Karl J., Salvatori, Tommaso, Isomura, Takuya, Tschantz, Alexander, Kiefer, Alex, Verbelen, Tim, Koudahl, Magnus, Paul, Aswin, Parr, Thomas, Razi, Adeel, Kagan, Brett, Buckley, Christopher L., Ramstead, Maxwell J. D.
Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the
Externí odkaz:
http://arxiv.org/abs/2312.07547
Autor:
Isomura, Takuya
Bayesian mechanics is a framework that addresses dynamical systems that can be conceptualised as Bayesian inference. However, the elucidation of requisite generative models is required for empirical applications to realistic self-organising systems.
Externí odkaz:
http://arxiv.org/abs/2311.10216
Autor:
Baltieri, Manuel, Isomura, Takuya
The Kalman filter is an algorithm for the estimation of hidden variables in dynamical systems under linear Gauss-Markov assumptions with widespread applications across different fields. Recently, its Bayesian interpretation has received a growing amo
Externí odkaz:
http://arxiv.org/abs/2111.10530
Autor:
Isomura, Takuya
The minimisation of cost functions is crucial in various optimisation fields. However, identifying their global minimum remains challenging owing to the huge computational cost incurred. This work analytically expresses the computational cost to iden
Externí odkaz:
http://arxiv.org/abs/2111.07680
Autor:
Friston, Karl J., Parr, Thomas, Heins, Conor, Constant, Axel, Friedman, Daniel, Isomura, Takuya, Fields, Chris, Verbelen, Tim, Ramstead, Maxwell, Clippinger, John, Frith, Christopher D.
Publikováno v:
In Neuroscience and Biobehavioral Reviews January 2024 156
Autor:
Isomura, Takuya, Toyoizumi, Taro
Publikováno v:
Nature Machine Intelligence 3, 434-446 (2021)
Generalization of time series prediction remains an important open issue in machine learning, wherein earlier methods have either large generalization error or local minima. We develop an analytically solvable, unsupervised learning scheme that extra
Externí odkaz:
http://arxiv.org/abs/2003.00470
Autor:
Isomura, Takuya
This work examines the expected computational cost to determine an approximate global minimum of a class of cost functions characterized by the variance of coefficients. The cost function takes $N$-dimensional binary states as arguments and has many
Externí odkaz:
http://arxiv.org/abs/1905.10017
Autor:
Yamaguchi, Ikuhiro, Isomura, Takuya, Nakao, Hiroya, Ogawa, Yutaro, Jimbo, Yasuhiko, Kotani, Kiyoshi
Publikováno v:
Journal of the Physical Society of Japan, 2019
We consider suppression of macroscopic synchronized oscillations in mixed populations of active and inactive oscillators with local diffusive coupling, described by a lattice complex Ginzburg-Landau model with discrete Laplacian in general dimensions
Externí odkaz:
http://arxiv.org/abs/1812.07659