Results 31 to 40 of about 1,634,787 (239)
Neural and phenotypic representation under the free-energy principle. [PDF]
Neurosci Biobehav Rev, 2021 Ramstead MJD +5 more
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A free-energy principle for representation learning [PDF]
Machine Learning: Science and Technology, 2021 Abstract This paper employs a formal connection of machine learning with thermodynamics to characterize the quality of learned representations for transfer learning. We discuss how information-theoretic functionals such as rate, distortion and classification loss of a model lie on a convex, so-called, equilibrium surface.
Yansong Gao, Pratik Chaudhari
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A free energy principle for the brain [PDF]
Journal of Physiology-Paris, 2006 By formulating Helmholtz's ideas about perception, in terms of modern-day theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts: using constructs from statistical physics, the problems of inferring the causes of sensory input and learning the causal structure of their ...
Karl, Friston +2 more
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Application of the Free Energy Principle to Estimation and Control [PDF]
IEEE Transactions on Signal Processing, 2021 Based on a generative model (GM) and beliefs over hidden states, the free energy principle (FEP) enables an agent to sense and act by minimizing a free energy bound on Bayesian surprise. Inclusion of prior beliefs in the GM about desired states leads to active inference (ActInf).
Thijs van de Laar +2 more
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The free energy principle induces neuromorphic development
Neuromorphic Computing and Engineering, 2022 Abstract We show how any finite physical system with morphological, i.e. three-dimensional embedding or shape, degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve over time towards a neuromorphic morphology that supports hierarchical computations in which each ‘level’ of the
Chris Fields 0001 +4 more
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Reinforced Imitation Learning by Free Energy Principle
CoRR, 2021 Reinforcement Learning (RL) requires a large amount of exploration especially in sparse-reward settings. Imitation Learning (IL) can learn from expert demonstrations without exploration, but it never exceeds the expert's performance and is also vulnerable to distributional shift between demonstration and execution.
Ryoya Ogishima +2 more
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Renormalization Group Flow and Thermodynamics of Conformal Field Theories [PDF]
, 1999 We discuss the free-energy density of bosonic and fermionic theories possessing strongly coupled critical points in D=3. We construct a stationary renormalization group trajectory which interpolates between the free massless theory of N scalars and a ...
Petkou, Anastasios C., Siopsis, George
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Natural language syntax complies with the free-energy principle. [PDF]
Synthese, 2021 Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the ...
Murphy E, Holmes E, Friston K.
europepmc +6 more sources
Philosophies, 2021 A weak version of the life-mind continuity thesis entails that every living system also has a basic mind (with a non-representational form of intentionality).
Wanja Wiese, Karl J. Friston
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First principles in the life sciences: The free-energy principle, organicism, and mechanism [PDF]
, 2017 The free-energy principle claims that biological systems behave adaptively maintaining their physical integrity only if they minimize the free energy of their sensory states.
Colombo, Matteo, Wright, Cory
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