Felix Dietrich
Felix Dietrich
Emmy Noether research group leader, Technical University of Munich
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Zitiert von
Zitiert von
Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
Q Li, F Dietrich, EM Bollt, IG Kevrekidis
Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (10), 2017
On learning Hamiltonian systems from data
T Bertalan, F Dietrich, I Mezić, IG Kevrekidis
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 2019
Gradient navigation model for pedestrian dynamics
F Dietrich, G Köster
Physical Review E 89 (6), 062801, 2014
Inter-Golgi transport mediated by COPI-containing vesicles carrying small cargoes
PA Pellett, F Dietrich, J Bewersdorf, JE Rothman, G Lavieu
Elife 2, e01296, 2013
The effect of stepping on pedestrian trajectories
MJ Seitz, F Dietrich, G Köster
Physica A: Statistical Mechanics and its Applications 421, 594-604, 2015
Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion
S Lee, F Dietrich, GE Karniadakis, IG Kevrekidis
Interface focus 9 (3), 20180083, 2019
Bridging the gap: From cellular automata to differential equation models for pedestrian dynamics
F Dietrich, G Köster, M Seitz, I von Sivers
Journal of Computational Science 5 (5), 841-846, 2014
On matching, and even rectifying, dynamical systems through koopman operator eigenfunctions
EM Bollt, Q Li, F Dietrich, I Kevrekidis
SIAM Journal on Applied Dynamical Systems 17 (2), 1925-1960, 2018
On the Koopman Operator of Algorithms
F Dietrich, TN Thiem, IG Kevrekidis
SIAM Journal on Applied Dynamical Systems 19 (2), 860-885, 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
Using Raspberry Pi for scientific video observation of pedestrians during a music festival
DH Biedermann, F Dietrich, O Handel, PM Kielar, M Seitz, 2015
A study of pedestrian stepping behaviour for crowd simulation
MJ Seitz, F Dietrich, G Köster
Transportation Research Procedia 2, 282-290, 2014
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
Some manifold learning considerations toward explicit model predictive control
RJ Lovelett, F Dietrich, S Lee, IG Kevrekidis
AIChE Journal 66 (5), e16881, 2020
Is Slowing Down Enough to Model Movement on Stairs?
G Köster, D Lehmberg, F Dietrich
Traffic and Granular Flow'15, 35-42, 2016
Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning
F Dietrich, A Makeev, G Kevrekidis, N Evangelou, T Bertalan, S Reich, ...
arXiv preprint arXiv:2106.09004, 2021
Learning the temporal evolution of multivariate densities via normalizing flows
Y Lu, R Maulik, T Gao, F Dietrich, IG Kevrekidis, J Duan
Chaos: An Interdisciplinary Journal of Nonlinear Science 32 (3), 2022
Learning emergent PDEs in a learned emergent space
FP Kemeth, T Bertalan, T Thiem, F Dietrich, SJ Moon, CR Laing, ...
arXiv preprint arXiv:2012.12738, 2020
datafold: data-driven models for point clouds and time series on manifolds
D Lehmberg, F Dietrich, G Köster, HJ Bungartz
Journal of Open Source Software 5 (51), 2283, 2020
The Superposition Principle: A Conceptual Perspective on Pedestrian Stream Simulations
MJ Seitz, F Dietrich, G Köster, HJ Bungartz
Collective Dynamics 1, 1-19, 2016
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