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Found 9 papers, 2 papers with code
A neural network account to Kant's philosophical aesthetics
In my reconstruction, the convergence of the GAN algorithm during the reception of art, either music or fine, entails the harmony of the faculties and thereby a neural network analogue of subjective purposefulness, i. e., beauty.
Quantum Tonality: A Mathemusical Playground
Fitting Gaussian Mixture Models (GMM) to the Krumhansl-Kessler (KK) probe tone profiles for static attraction opens the possibility to investigate the underlying wave function as the stationary ground state of an anharmonic quantum oscillator with a schematic Hamiltonian involving a perturbation potential.
Invariants for neural automata
Our work could be of substantial importance for related regression studies of real-world measurements with neurosymbolic processors for avoiding confounding results that are dependant on a particular encoding and not intrinsic to the dynamics.
Machine Semiotics
For speech assistive devices, the learning of machine-specific meanings of human utterances, i. e. the fossilization of conversational implicatures into conventionalized ones by trial and error through lexicalization appears to be sufficient.
Reinforcement learning of minimalist grammars
In order to develop proper cognitive information and communication technologies, simple slot-filling should be replaced by utterance meaning transducers (UMT) that are based on semantic parsers and a mental lexicon, comprising syntactic, phonetic and semantic features of the language under consideration.
Vector symbolic architectures for context-free grammars
Our approach could leverage the development of VSA for explainable artificial intelligence (XAI) by means of hyperdimensional deep neural computation.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Reinforcement Learning of Minimalist Numeral Grammars
In order to develop proper cognitive information and communication technologies, simple slot-filling should be replaced by utterance meaning transducers (UMT) that are based on semantic parsers and a \emph{mental lexicon}, comprising syntactic, phonetic and semantic features of the language under consideration.
A modular architecture for transparent computation in Recurrent Neural Networks
We then show that the Goedelization of versatile shifts defines nonlinear dynamical automata, dynamical systems evolving on a vectorial space.
Turing Computation with Recurrent Artificial Neural Networks
We improve the results by Siegelmann & Sontag (1995) by providing a novel and parsimonious constructive mapping between Turing Machines and Recurrent Artificial Neural Networks, based on recent developments of Nonlinear Dynamical Automata.
