Tom Bertalan

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Ioannis KevrekidisJohns Hopkins UniversityVerified email at jhu.edu
Felix DietrichProfessor for Physics-Enhanced Machine Learning, Technical University of MunichVerified email at tum.de
Felix P. KemethResearcher, Johns Hopkins UniversityVerified email at jh.edu
Carlo LaingProfessor of Nonlinear Mathematics, Massey UniversityVerified email at massey.ac.nz
Igor MezicUniversity of California, Santa BarbaraVerified email at ucsb.edu
Erik BolltClarkson UniversityVerified email at clarkson.edu
Ronen TalmonAssociate Professor, EE Department, TechnionVerified email at ee.technion.ac.il
Mahdi KooshkbaghiVerified email at cshl.edu
Anders JosefssonUniversity of Pittsburgh, Pittsburgh PA, USAVerified email at pitt.edu
Stavroula SofouJohns Hopkins UniversityVerified email at jhu.edu
Akand IslamSchrodingerVerified email at schrodinger.com
Qianxiao LiAssistant Professor, Department of Mathematics and Institute for Functional Intelligent MaterialsVerified email at nus.edu.sg
Ofir LindenbaumAssistant Professor at Bar Ilan UniversityVerified email at biu.ac.il
Matan GavishAssociate Professor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il
Erez PeterfreundPhD student in computer scienceVerified email at cs.huji.ac.il
Ronald Coifmanprofessor of mathematics yale universityVerified email at math.yale.edu
Tianqi CuiJohns Hopkins UniversityVerified email at jhu.edu
Yan WuComputational Scientist, Altos LabsVerified email at altoslabs.com
Yorgos M. PsarellisPostdoctoral Researcher, Massachusetts Institute of TechnologyVerified email at mit.edu
Saurabh MalaniPhD Candidate, Princeton UniversityVerified email at princeton.edu

Tom Bertalan

Chemical and Biomolecular Engineering, Johns Hopkins University

Verified email at jhu.edu - Homepage

dynamical systems robotics manifold learning computational neuroscience


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
On learning Hamiltonian systems from data T Bertalan, F Dietrich, I Mezić, IG Kevrekidis Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 2019	137	2019
Alpha-particle radiotherapy: For large solid tumors diffusion trumps targeting C Zhu, M Sempkowski, T Holleran, T Linz, T Bertalan, A Josefsson, ... Biomaterials 130, 67-75, 2017	42	2017
Emergent spaces for coupled oscillators TN Thiem, M Kooshkbaghi, T Bertalan, CR Laing, IG Kevrekidis Frontiers in computational neuroscience 14, 36, 2020	25	2020
An emergent space for distributed data with hidden internal order through manifold learning FP Kemeth, SW Haugland, F Dietrich, T Bertalan, K Höhlein, Q Li, ... IEEE Access 6, 77402-77413, 2018	25	2018
Local conformal autoencoder for standardized data coordinates E Peterfreund, O Lindenbaum, F Dietrich, T Bertalan, M Gavish, ... Proceedings of the National Academy of Sciences 117 (49), 30918-30927, 2020	22	2020
Coarse-Grained Descriptions of Dynamics for Networks with both Intrinsic and Structural Heterogeneities IGK Tom Bertalan, Yan Wu, Carlo Laing, C William Gear Frontiers in Computational Neuroscience, 2017	11	2017
Dimension reduction in heterogeneous neural networks: generalized Polynomial Chaos (gPC) and ANalysis-Of-VAriance (ANOVA) M Choi, T Bertalan, CR Laing, IG Kevrekidis The European Physical Journal Special Topics 225, 1165-1180, 2016	11	2016
nSpyres, An OpenSource, Python Based Framework for Simulation of Flow through Porous Media ES Carlson, AW Islam, F Dumkwu, TS Bertalan 4th International Conference on Porous Media and Annual Meeting of the …, 2012	10	2012
OpenMG: a new multigrid implementation in Python TS Bertalan, AW Islam, RB Sidje, ES Carlson Numerical Linear Algebra with Applications 21 (5), 685-700, 2014	6	2014
An equal space for complex data with unknown internal order: Observability, gauge invariance and manifold learning FP Kemeth, SW Haugland, F Dietrich, T Bertalan, Q Li, EM Bollt, R Talmon, ... arXiv preprint arXiv:1708.05406, 2017	2	2017
Learning Partial Differential Equations in Emergent Coordinates F Kemeth, T Bertalan, T Thiem, IG Kevrekidis 2021 AIChE Annual Meeting, 2021	1	2021
Certified Invertibility in Neural Networks via Mixed-Integer Programming T Cui, T Bertalan, GJ Pappas, M Morari, Y Kevrekidis, M Fazlyab Learning for Dynamics and Control Conference, 483-496, 2023		2023
Tipping Point Dynamics for Epidemiological Networks. Constructing Reduced Dynamical Data-Driven Models for Evolving Graphs N Evangelou, T Cui, J Bello-Rivas, A Makeev, T Bertalan, IG Kevrekidis 2022 AIChE Annual Meeting, 2022		2022
A Data-Driven Approach to Determining Problem Well-Posedness T Bertalan, E Rebrova, G Kevrekidis, IG Kevrekidis 2022 AIChE Annual Meeting, 2022		2022
Some of the Variables, Some of the Times, with Some Things Known: Identification with Partial Information S Malani, T Bertalan, T Cui, M Betenbaugh, J Avalos, IG Kevrekidis 2022 AIChE Annual Meeting, 2022		2022
Manifold Learning Post-Processing Galerkin Algorithms for Dissipative PDEs on Their Approximate Inertial Manifolds CM Linares, T Bertalan, N Evangelou, ES Titi, IG Kevrekidis 2022 AIChE Annual Meeting, 2022		2022
Quantifying the Invertibility of Neural Networks and Their Transformations T Cui, T Bertalan, IG Kevrekidis, M Fazlyab 2022 AIChE Annual Meeting, 2022		2022
Inverse Backward Analysis of Neural Approximants of Ordinary Differential Equations T Bertalan, A Zhu, B Zhu, Y Tang, IG Kevrekidis 2022 AIChE Annual Meeting, 2022		2022
Addressing Well-Posedness in a Data-Driven Manner: Model Problems and Physics-Informed Neural Networks T Bertalan, G Kevrekidis, S Mishra, IG Kevrekidis 2021 AIChE Annual Meeting, 2021		2021
Data-Driven Development of Approximate Inertial Forms and Closures for Coarse-Scale Modeling of Multiphase Flows CM Linares, T Bertalan, S Lee, J Lu, G Tryggvason, IG Kevrekidis 2021 AIChE Annual Meeting, 2021		2021

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