Defining Quantum Neural Networks via Quantum Time Evolution

Autor: Dendukuri, Aditya, Keeling, Blake, Fereidouni, Arash, Burbridge, Joshua, Luu, Khoa, Churchill, Hugh

This work presents a novel fundamental algorithm for for defining and training Neural Networks in Quantum Information based on time evolution and the Hamiltonian. Classical Neural Network algorithms (ANN) are computationally expensive. For example, i

Externí odkaz: http://arxiv.org/abs/1905.10912

Machine learning to identify variables in thermodynamically small systems

Autor: Ford, David M., Dendukuri, Aditya, Kalyoncu, Gülce, Luu, Khoa, Patitz, Matthew J.

Publikováno v: In Computers and Chemical Engineering 4 October 2020 141

Protosequences in human cortical organoids model intrinsic states in the developing cortex.

Autor: van der Molen T; Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA.; Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106, USA., Spaeth A; UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA.; Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA., Chini M; Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany., Bartram J; Department of Biosystems Science and Engineering, ETH Zürich, Klingelbergstrasse 48, 4056 Basel, Switzerland., Dendukuri A; Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA., Zhang Z; Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106., Bhaskaran-Nair K; Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA., Blauvelt LJ; UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA., Petzold LR; Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA., Hansma PK; Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA.; Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106., Teodorescu M; UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA.; Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA., Hierlemann A; Department of Biosystems Science and Engineering, ETH Zürich, Klingelbergstrasse 48, 4056 Basel, Switzerland., Hengen KB; Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA., Hanganu-Opatz IL; Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany., Kosik KS; Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA.; Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106, USA., Sharf T; UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA.; Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.; Institute for the Biology of Stem Cells, University of California Santa Cruz, Santa Cruz, CA 95064, USA.

Publikováno v: BioRxiv : the preprint server for biology [bioRxiv] 2023 Dec 30. Date of Electronic Publication: 2023 Dec 30.