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ORCIDAlex A. Gorodetsky
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- affiliation: University of Michigan, USA
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2020 – today
- 2024
[j15]Thomas O. Dixon, James E. Warner, Geoffrey F. Bomarito, Alex A. Gorodetsky:
Covariance Expressions for Multifidelity Sampling with Multioutput, Multistatistic Estimators: Application to Approximate Control Variates. SIAM/ASA J. Uncertain. Quantification 12(3): 1005-1049 (2024)- [j14]Doruk Aksoy
, David J. Gorsich, Shravan K. Veerapaneni, Alex A. Gorodetsky:
An Incremental Tensor Train Decomposition Algorithm. SIAM J. Sci. Comput. 46(2): 1047- (2024) - [j13]Brian Chen, Doruk Aksoy, David J. Gorsich, Shravan K. Veerapaneni, Alex A. Gorodetsky:
Low-Rank Tensor-Network Encodings for Video-to-Action Behavioral Cloning. Trans. Mach. Learn. Res. 2024 (2024) - [i15]Nicholas Galioto, Harsh Sharma, Boris Kramer, Alex Arkady Gorodetsky:
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling. CoRR abs/2401.12476 (2024) - [i14]Alex A. Gorodetsky, John D. Jakeman, Michael S. Eldred:
Grouped approximate control variate estimators. CoRR abs/2402.14736 (2024) - [i13]Joshua Pickard, Marc Andrew Choi, Natalie Oliven, Cooper Stansbury, Jillian Cwycyshyn, Nicholas Galioto, Alex A. Gorodetsky, Alvaro Velasquez, Indika Rajapakse:
Bioinformatics Retrieval Augmentation Data (BRAD) Digital Assistant. CoRR abs/2409.02864 (2024) - 2023
- [j12]Hadi Salehi, Alex A. Gorodetsky, Roya Solhmirzaei, Pengcheng Jiao:
High-dimensional data analytics in civil engineering: A review on matrix and tensor decomposition. Eng. Appl. Artif. Intell. 125: 106659 (2023) - 2022
- [j11]Alex A. Gorodetsky, Cosmin Safta, John D. Jakeman:
Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning. J. Mach. Learn. Res. 23: 143:1-143:29 (2022) - [j10]Trung Pham, Alex A. Gorodetsky:
Ensemble Approximate Control Variate Estimators: Applications to MultiFidelity Importance Sampling. SIAM/ASA J. Uncertain. Quantification 10(1): 1250-1292 (2022) - [j9]Doruk Aksoy, Silas Alben, Robert D. Deegan, Alex A. Gorodetsky:
Inverse design of self-oscillatory gels through deep learning. Neural Comput. Appl. 34(9): 6879-6905 (2022) - [j8]Koray Gabriel Kachar, Alex Arkady Gorodetsky:
Dynamic Multiagent Assignment Via Discrete Optimal Transport. IEEE Trans. Control. Netw. Syst. 9(1): 151-162 (2022) - [c11]Harsh Sharma, Nicholas Galioto, Alex A. Gorodetsky, Boris Kramer:
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models. CDC 2022: 6742-6749 - [i12]Harsh Sharma, Nicholas Galioto, Alex A. Gorodetsky, Boris Kramer:
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models. CoRR abs/2209.07646 (2022) - [i11]Doruk Aksoy, David J. Gorsich, Shravan K. Veerapaneni, Alex A. Gorodetsky:
An Incremental Tensor Train Decomposition Algorithm. CoRR abs/2211.12487 (2022) - [i10]Nicholas Galioto, Alex Arkady Gorodetsky:
Robust identification of non-autonomous dynamical systems using stochastic dynamics models. CoRR abs/2212.13902 (2022) - 2021
- [c10]Brian Chen, Siddhant Tandon, David J. Gorsich, Alex A. Gorodetsky, Shravan K. Veerapaneni:
Behavioral Cloning in Atari Games Using a Combined Variational Autoencoder and Predictor Model. CEC 2021: 2077-2084 - [c9]Xunbi A. Ji, Tamás G. Molnár, Alex A. Gorodetsky, Gábor Orosz:
Bayesian Inference for Time Delay Systems with Application to Connected Automated Vehicles. ITSC 2021: 3259-3264 - [c8]Nicholas Galioto, Alex Arkady Gorodetsky:
A New Objective for Identification of Partially Observed Linear Time-Invariant Dynamical Systems from Input-Output Data. L4DC 2021: 1180-1191 - 2020
- [j7]Alex A. Gorodetsky, Gianluca Geraci, Michael S. Eldred, John D. Jakeman:
A generalized approximate control variate framework for multifidelity uncertainty quantification. J. Comput. Phys. 408: 109257 (2020) - [c7]Hang Yang, Narayanan Kidambi, Yuji Fujii, Alex A. Gorodetsky, Kon-Well Wang:
Uncertainty Quantification Using Generalized Polynomial Chaos for Online Simulations of Automotive Propulsion Systems. ACC 2020: 295-300 - [c6]Nicholas Galioto, Alex A. Gorodetsky:
Bayesian Identification of Hamiltonian Dynamics from Symplectic Data. CDC 2020: 1190-1195 - [i9]Nicholas Galioto, Alex A. Gorodetsky:
Bayesian System ID: Optimal management of parameter, model, and measurement uncertainty. CoRR abs/2003.02359 (2020) - [i8]Saibal De, Hadi Salehi, Alex A. Gorodetsky:
Efficient MCMC Sampling for Bayesian Matrix Factorization by Breaking Posterior Symmetries. CoRR abs/2006.04295 (2020) - [i7]Alex A. Gorodetsky, John D. Jakeman, Gianluca Geraci:
MFNets: Learning network representations for multifidelity surrogate modeling. CoRR abs/2008.02672 (2020)
2010 – 2019
- 2019
- [j6]Silas Alben, Alex A. Gorodetsky, Donghak Kim, Robert D. Deegan:
Semi-implicit methods for the dynamics of elastic sheets. J. Comput. Phys. 399 (2019) - [i6]Prashant Rai, Hemanth Kolla, Lewis Cannada, Alex A. Gorodetsky:
Randomized Functional Sparse Tucker Tensor for Compression and Fast Visualization of Scientific Data. CoRR abs/1907.05884 (2019) - [i5]John D. Jakeman, Michael Eldred, Gianluca Geraci, Alex A. Gorodetsky:
Adaptive Multi-index Collocation for Uncertainty Quantification and Sensitivity Analysis. CoRR abs/1909.13845 (2019) - [i4]Koray Gabriel Kachar, Alex A. Gorodetsky:
Dynamic multi-agent assignment via discrete optimal transport. CoRR abs/1910.10748 (2019) - 2018
- [j5]Alex A. Gorodetsky, Sertac Karaman, Youssef M. Marzouk:
High-dimensional stochastic optimal control using continuous tensor decompositions. Int. J. Robotics Res. 37(2-3): 340-377 (2018) - [j4]Alex A. Gorodetsky, John D. Jakeman:
Gradient-based optimization for regression in the functional tensor-train format. J. Comput. Phys. 374: 1219-1238 (2018) - [j3]Boris Kramer, Alex A. Gorodetsky:
System Identification via CUR-Factored Hankel Approximation. SIAM J. Sci. Comput. 40(2) (2018) - [c5]Ezra Tal, Alex A. Gorodetsky, Sertac Karaman:
Continuous Tensor Train-Based Dynamic Programming for High-Dimensional Zero-Sum Differential Games. ACC 2018: 6086-6093 - [c4]Thomas Sayre-McCord, Winter Guerra, Amado Antonini, Jasper Arneberg, Austin Brown, Guilherme Venturelli Cavalheiro, Yajun Fang, Alex A. Gorodetsky, Dave McCoy, Sebastian Quilter, Fabian Riether, Ezra Tal, Yunus Terzioglu, Luca Carlone, Sertac Karaman:
Visual-Inertial Navigation Algorithm Development Using Photorealistic Camera Simulation in the Loop. ICRA 2018: 2566-2573 - 2017
- [c3]Alex A. Gorodetsky, Sertac Karaman, Youssef M. Marzouk:
Low-rank tensor integration for Gaussian filtering of continuous time nonlinear systems. CDC 2017: 2789-2794 - 2016
- [j2]Alex A. Gorodetsky, Youssef M. Marzouk:
Mercer Kernels and Integrated Variance Experimental Design: Connections Between Gaussian Process Regression and Polynomial Approximation. SIAM/ASA J. Uncertain. Quantification 4(1): 796-828 (2016) - [c2]John Irvin Alora, Alex A. Gorodetsky, Sertac Karaman, Youssef M. Marzouk, Nathan Lowry:
Automated synthesis of low-rank control systems from sc-LTL specifications using tensor-train decompositions. CDC 2016: 1131-1138 - [i3]Alex A. Gorodetsky, Sertac Karaman, Youssef M. Marzouk:
High-Dimensional Stochastic Optimal Control using Continuous Tensor Decompositions. CoRR abs/1611.04706 (2016) - 2015
- [c1]Alex A. Gorodetsky, Sertac Karaman, Youssef M. Marzouk:
Efficient High-Dimensional Stochastic Optimal Motion Control using Tensor-Train Decomposition. Robotics: Science and Systems 2015 - [i2]Alex A. Gorodetsky, Youssef M. Marzouk:
Mercer kernels and integrated variance experimental design: connections between Gaussian process regression and polynomial approximation. CoRR abs/1503.00021 (2015) - 2014
- [j1]Alex A. Gorodetsky, Youssef M. Marzouk:
Efficient Localization of Discontinuities in Complex Computational Simulations. SIAM J. Sci. Comput. 36(6) (2014) - [i1]Alex A. Gorodetsky, Youssef M. Marzouk:
Efficient Localization of Discontinuities in Complex Computational Simulations. CoRR abs/1402.2845 (2014)
Coauthor Index
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last updated on 2024-10-07 01:21 CEST by the dblp team
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