Add to ORKGThe human brain is a complex system composed of a network of hundreds of billions of dis-crete neurons that are coupled through time dependent synapses. Simulating the entire brain is a daunting challenge. Here, we show how ideas from quantum field theory can be used to construct an effective reduced theory, which may be analyzed with lattice computations. We give some examples of how the formalism can be applied to biophysically plausible neural network models. The 32nd International Symposium on Lattice Field Theor
Progress in answering some of the most interesting open questions about the nature of reality is cur...
We present a mathematical implementation of a quantum mechanical artificial neural network, in the q...
As the end of Moore’s law nears and the energy demand for computing increases the search for alterna...
This paper makes two self-confessedly ambitious proposals. One is a theory of mind and world with an...
The transition to Euclidean space and the discretization of quantum field theories on spatial or spa...
The precise equivalence between discretized Euclidean field theories and a certain class of probabil...
In this paper, we will discuss a formal link between neural networks and quantum computing. For that...
Based on quantum biology and biological gauge field theory, we propose the biological lattice gauge ...
With this book, the editors present the first comprehensive collection in neural field studies, auth...
Mathematical modelling of the macroscopic electrical activity of the brain ishighly non-trivial and ...
International audienceA statistical ensemble of neural networks can be described in terms of a quant...
We present a physical interpretation of machine learning functions, opening up the possibility to co...
This report reviews the basic principles of field computation, a model of massively parallel analog ...
Can we reduce Quantum Field Theory (QFT) to a quantum computation? Can physics be simulated by a qua...
We explicitly construct the quantum field theory corresponding to a general class of deep neural net...
Progress in answering some of the most interesting open questions about the nature of reality is cur...
We present a mathematical implementation of a quantum mechanical artificial neural network, in the q...
As the end of Moore’s law nears and the energy demand for computing increases the search for alterna...
This paper makes two self-confessedly ambitious proposals. One is a theory of mind and world with an...
The transition to Euclidean space and the discretization of quantum field theories on spatial or spa...
The precise equivalence between discretized Euclidean field theories and a certain class of probabil...
In this paper, we will discuss a formal link between neural networks and quantum computing. For that...
Based on quantum biology and biological gauge field theory, we propose the biological lattice gauge ...
With this book, the editors present the first comprehensive collection in neural field studies, auth...
Mathematical modelling of the macroscopic electrical activity of the brain ishighly non-trivial and ...
International audienceA statistical ensemble of neural networks can be described in terms of a quant...
We present a physical interpretation of machine learning functions, opening up the possibility to co...
This report reviews the basic principles of field computation, a model of massively parallel analog ...
Can we reduce Quantum Field Theory (QFT) to a quantum computation? Can physics be simulated by a qua...
We explicitly construct the quantum field theory corresponding to a general class of deep neural net...
Progress in answering some of the most interesting open questions about the nature of reality is cur...
We present a mathematical implementation of a quantum mechanical artificial neural network, in the q...
As the end of Moore’s law nears and the energy demand for computing increases the search for alterna...