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Nicholas Galioto
Nicholas Galioto
Engineering Postdoc, University of Michigan
Correu electrònic verificat a umich.edu - Pàgina d'inici
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Ultralow frequency electrochemical–mechanical strain energy harvester using 2D black phosphorus nanosheets
N Muralidharan, M Li, RE Carter, N Galioto, CL Pint
ACS Energy Letters 2 (8), 1797-1803, 2017
742017
Bayesian system ID: optimal management of parameter, model, and measurement uncertainty
N Galioto, AA Gorodetsky
Nonlinear Dynamics 102 (1), 241-267, 2020
392020
From the junkyard to the power grid: ambient processing of scrap metals into nanostructured electrodes for ultrafast rechargeable batteries
N Muralidharan, AS Westover, H Sun, N Galioto, RE Carter, AP Cohn, ...
ACS Energy Letters 1 (5), 1034-1041, 2016
132016
Bayesian identification of Hamiltonian dynamics from symplectic data
N Galioto, AA Gorodetsky
2020 59th IEEE Conference on Decision and Control (CDC), 1190-1195, 2020
122020
A new objective for identification of partially observed linear time-invariant dynamical systems from input-output data
N Galioto, AA Gorodetsky
Learning for Dynamics and Control, 1180-1191, 2021
42021
Likelihood-based generalization of Markov parameter estimation and multiple shooting objectives in system identification
N Galioto, AA Gorodetsky
Physica D: Nonlinear Phenomena 462, 134146, 2024
3*2024
Bayesian identification of nonseparable Hamiltonian systems using stochastic dynamic models
H Sharma, N Galioto, AA Gorodetsky, B Kramer
2022 IEEE 61st Conference on Decision and Control (CDC), 6742-6749, 2022
32022
Language Model Powered Digital Biology
J Pickard, MA Choi, N Oliven, C Stansbury, J Cwycyshyn, N Galioto, ...
arXiv preprint arXiv:2409.02864, 2024
2*2024
A switching Kalman filter approach to online mitigation and correction sensor corruption for inertial navigation
A Mustaev, N Galioto, M Boler, JD Jakeman, C Safta, A Gorodetsky
arXiv preprint arXiv:2412.06601, 2024
2024
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling
N Galioto, H Sharma, B Kramer, AA Gorodetsky
Computer Methods in Applied Mechanics and Engineering 430, 117194, 2024
2024
Generalization of System Identification Objective Functions Through Stochastic Hidden Markov Models for Regularization, Smoothness, and Uncertainty Quantification
N Galioto
2023
From the Junkyard to the Power Grid: Ambient Processing of Scrap Metals into Nanostructured Electrodes for Ultrafast Rechargeable Batteries
AS Westover, N Muralidharan, H Sun, N Galioto, RE Carter, AP Cohn, ...
DOCTOR OF PHILOSOPHY in Interdisciplinary Materials Science and Engineering …, 2016
2016
METHODS AND APPROACHES TO BENCHMARK DATA-DRIVEN MODELING IN THE SPARSE AND NOISY DATA REGIMES
A Gorodetsky, N Galioto
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
Articles 1–13