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Mikkel N Schmidt

Showing results (1-10 of 17) with videos related to

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Neural Computation|April 19, 2012
Bayesian community detectionMorten Mørup, Mikkel N Schmidt
Computational Intelligence and Neuroscience|May 10, 2008
Nonnegative matrix factorization with Gaussian process priorsMikkel N Schmidt, Hans Laurberg
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|October 15, 2014
Infinite-degree-corrected stochastic block modelTue Herlau, Mikkel N Schmidt, Morten Mørup
The Analyst|April 27, 2022
Raman spectrum matching with contrastive representation learningBo Li, Mikkel N Schmidt, Tommy S Alstrøm
Molecular Informatics|February 7, 2018
Deep Generative Models for Molecular SciencePeter B Jørgensen, Mikkel N Schmidt, Ole Winther
Neural Computation|August 5, 2017
Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI DataRasmus E Røge, Kristoffer H Madsen, Mikkel N Schmidt, et al.
Neuroimage|January 3, 2018
Predictive assessment of models for dynamic functional connectivitySøren F V Nielsen, Mikkel N Schmidt, Kristoffer H Madsen, et al.
Physical Chemistry Chemical Physics : PCCP|September 19, 2023
Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forcesJonas Busk, Mikkel N Schmidt, Ole Winther, et al.
The Analyst|August 21, 2023
Nitroaromatic explosives' detection and quantification using an attention-based transformer on surface-enhanced Raman spectroscopy mapsBo Li, Giulia Zappalá, Elodie Dumont, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|May 9, 2019
Deep Learning Spectroscopy: Neural Networks for Molecular Excitation SpectraKunal Ghosh, Annika Stuke, Milica Todorović, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Neural Computation|April 19, 2012
Bayesian community detectionMorten Mørup, Mikkel N Schmidt
Computational Intelligence and Neuroscience|May 10, 2008
Nonnegative matrix factorization with Gaussian process priorsMikkel N Schmidt, Hans Laurberg
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|October 15, 2014
Infinite-degree-corrected stochastic block modelTue Herlau, Mikkel N Schmidt, Morten Mørup
The Analyst|April 27, 2022
Raman spectrum matching with contrastive representation learningBo Li, Mikkel N Schmidt, Tommy S Alstrøm
Molecular Informatics|February 7, 2018
Deep Generative Models for Molecular SciencePeter B Jørgensen, Mikkel N Schmidt, Ole Winther
Neural Computation|August 5, 2017
Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI DataRasmus E Røge, Kristoffer H Madsen, Mikkel N Schmidt, et al.
Neuroimage|January 3, 2018
Predictive assessment of models for dynamic functional connectivitySøren F V Nielsen, Mikkel N Schmidt, Kristoffer H Madsen, et al.
Physical Chemistry Chemical Physics : PCCP|September 19, 2023
Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forcesJonas Busk, Mikkel N Schmidt, Ole Winther, et al.
The Analyst|August 21, 2023
Nitroaromatic explosives' detection and quantification using an attention-based transformer on surface-enhanced Raman spectroscopy mapsBo Li, Giulia Zappalá, Elodie Dumont, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|May 9, 2019
Deep Learning Spectroscopy: Neural Networks for Molecular Excitation SpectraKunal Ghosh, Annika Stuke, Milica Todorović, et al.
Pageof 2