Publication list

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In review:

  1. Leon Herrmann, Tim Bürchner, Felix Dietrich, Stefan Kollmannsberger, “On the Use of Neural Networks for Full Waveform Inversion”, submitted (2023). arXiv
  2. Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis, “A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms”, submitted (2022). arXiv
  3. Irene López Gutiérrez, Felix Dietrich, and Christian B Mendl, “Quantum Process Tomography of Unitary Maps from Time-Delayed Measurements”, submitted (2022). arXiv
  4. Felix Dietrich, Juan M. Bello-Rivas, and Ioannis G. Kevrekidis, “On the Correspondence between Gaussian Processes and Geometric Harmonics,” submitted (2021). arXiv
  5. Or Yair, Felix Dietrich, Ronen Talmon, and Ioannis G. Kevrekidis, “Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation,” submitted (2021). arXiv
  6. Tom Bertalan, Felix Dietrich, Ioannis G. Kevrekidis, “Transformations between deep neural networks,” submitted (2020). arXiv

2023

  1. Felix Dietrich, Alexei Makeev, George Kevrekidis, Nikolaos Evangelou, Tom Bertalan, Sebastian Reich, and Ioannis G. Kevrekidis, “Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning,” Chaos, vol. 33, no. 2, p. 023121, Feb. 2023. arXiv DOI

2022

  1. Felix P. Kemeth, Tom Bertalan, Thomas Thiem, Felix Dietrich, Sung Joon Moon, Carlo R. Laing, and Ioannis G. Kevrekidis, “Learning emergent PDEs in a learned emergent space,” Nature Communications (13 (1), 1-13, 2022). arXiv, DOI
  2. Nikolaos Evangelou, Noah J. Wichrowski, George A. Kevrekidis, Felix Dietrich, Mahdi Kooshkbaghi, Sarah McFann, Ioannis G. Kevrekidis, “On the Parameter Combinations That Matter and on Those That do Not,” PNAS (2022). arXiv, DOI
  3. Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, and Qianxiao Li, “Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators,” SIAM Journal on Scientific Computing (2022). arXiv, DOI
  4. Philipp Scholl, Felix Dietrich, Clemens Otte, and Steffen Udluft, “Safe Policy Improvement Approaches on Discrete Markov Decision Processes,” ICAART 2022. arXiv conference
  5. Lubin Yu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, and Jinqiao Duan, “Learning the temporal evolution of multivariate densities via normalizing flows,” Chaos, no. 32, p. 033121, 2022. arXiv DOI
  6. Felix Dietrich, Or Yair, Rotem Mulayoff, Ronen Talmon, and Ioannis G. Kevrekidis, “Spectral Discovery of Jointly Smooth Features for Multimodal Data,”  SIAM Journal on Mathematics of Data Science, 4(1). (2022). arXiv, DOI

2021

  1. Daniel Lehmberg, Felix Dietrich, Gerta Köster, “Modeling Melburnians—Using the Koopman operator to gain insight into crowd dynamics,” Transportation Research Part C: Emerging Technologies, Elsevier BV, 2021, 133, 103437. DOI

2020

  1. Daniel Lehmberg, Felix Dietrich, Gerta Köster, Hans-Joachim Bungartz, “datafold: data-driven models for point clouds and time series on manifolds,” Journal of Open Source Software 5 (51), 2283. DOI
  2. Erez Peterfreund, Ofir Lindenbaum, Felix Dietrich, Tom Bertalan, Matan Gavish, Ioannis G. Kevrekidis and Ronald R. Coifman, “Local conformal autoencoder for standardized data coordinates,” PNAS 117 (49) 30918-30927 (2020). arXiv, DOI
  3. Caroline Moosmüller, Felix Dietrich, Ioannis G. Kevrekidis, “A geometric approach to the transport of discontinuous densities,” SIAM J. Uncertainty Quantification, 8(3), 1012–1035. arXiv DOI
  4. Felix Dietrich, Mahdi Kooshkbaghi, Erik M. Bollt, and Ioannis G. Kevrekidis, “Manifold Learning for Organizing Unstructured Sets of Process Observations,” Chaos, 30, 043108. arXiv DOI
  5. Felix Dietrich, Thomas N. Thiem, Ioannis G. Kevrekidis, “On the Koopman operator of algorithms,” SIAM J. Appl. Dyn. Syst., 19(2), 860–885. arXiv DOI
  6. Robert J. Lovelett, Felix Dietrich, Seungjoon Lee, and Ioannis G. Kevrekidis, “Some manifold learning considerations towards explicit model predictive control,” AIChE Journal 66 (5), e16881. arXiv DOI
  7. Florian Künzner, Tobias Neckel, Hans-Joachim Bungartz, Felix Dietrich, Gerta Köster, “Efficient Quantification of Model Uncertainties When De-boarding a Train,” Collective Dynamics (5); Proceedings from the 9th International Conference on Pedestrian and Evacuation Dynamics (PED2018). DOI

2019

  1. Tom Bertalan, Felix Dietrich, Igor Mezić, and Ioannis G. Kevrekidis, “On learning Hamiltonian systems from data,” Chaos, 29, 121107. arXiv DOI
  2. Seungjoon Lee, Felix Dietrich, George E. Karniadakis, and Ioannis G. Kevrekidis, “Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion,” Interface Focus, The Royal Society, 9, 20180083. DOI, arXiv
  3. Daniel Lehmberg, Felix Dietrich, Ioannis G. Kevrekidis, Hans-Joachim Bungartz, Gerta Köster, “Exploring Koopman Operator Based Surrogate Models Accelerating Analysis of Critical Pedestrian Densities,” Traffic and Granular Flow (TGF) in Pamplona, Spain Conference talk (Daniel Lehmberg) (2019). Conference

2018

  1. Erik M. Bollt, Qianxiao Li, Felix Dietrich, Ioannis G. Kevrekidis, “On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions,” SIAM Journal on Applied Dynamical Systems, 17, 1925-1960. DOI
  2. Felix Dietrich, Florian Künzner, Tobias Neckel, Gerta Köster, Hans-Joachim Bungartz, “Fast and flexible uncertainty quantification through a data-driven surrogate model,” IJUQ, pp. 175-192. DOI
  3. Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich, Tom Bertalan, Qianxiao Li, Erik M. Bollt, Ronen Talmon, Katharina Krischer, and Ioannis G. Kevrekidis, “An Emergent Space for Distributed Data with Hidden Internal Order through Manifold Learning,” IEEE Access, 6, pp. 77402-77413. DOI

2017

  1. Felix Dietrich, “Data-Driven Surrogate Models for Dynamical Systems,” PhD thesis, Technical University of Munich. mediaTUM PDF
  2. Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich, Tom Bertalan, Qianxiao Li, Erik M. Bollt, Ronen Talmon, Katharina Krischer, and Ioannis G. Kevrekidis, “An Equal Space for Complex Data with Unknown Internal Order: Observability, Gauge Invariance and Manifold Learning,” arXiv
  3. Qianxiao Li, Felix Dietrich, Erik M. Bollt, and Ioannis G. Kevrekidis, “Extended dynamic mode decomposition with dictionary learning: a data-driven adaptive spectral decomposition of the Koopman operator,” Chaos, 27, 103111. DOI

2016

  1. Felix Dietrich, Florian Albrecht, and Gerta Köster: Surrogate Models for Bottleneck Scenarios. Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016), Springer. DOI
  2. Felix Dietrich, Gerta Köster, and Hans-Joachim Bungartz: Numerical Model Construction with Closed Observables. SIAM Journal on Applied Dynamical Systems, 15, pp. 2078-2108. DOI
  3. Michael J. Seitz, Felix Dietrich, Gerta Köster, and Hans-Joachim Bungartz: The superposition principle: A conceptual perspective on pedestrian stream simulations. Collective Dynamics, 1, A2. DOI

2015

  1. Michael J. Seitz, Felix Dietrich, and Gerta Köster: The effect of stepping on pedestrian trajectories. Physica A: Statistical Mechanics and its Applications, 421, 594-60. DOI
  2. Daniel H. Biedermann, Felix Dietrich, Oliver Handel, Peter M. Kielar, Michael Seitz: Using Raspberry Pi for scientific video observation of pedestrians during a music festival. Technical Report, TUM. PDF, arXiv
  3. Peter M. Kielar, Daniel H. Biedermann, and Felix Dietrich: Gentle Coupling of Pedestrian Behavior Model Implementations: a Pedestrian Simulator Interoperability Protocol. Forum Bau, TUM. PDF
  4. Felix Dietrich, Stefan Disselnkötter, and Gerta Köster: How to get a model in pedestrian dynamics to produce stop and go waves? Traffic and Granular Flow ’15, Springer International Publishing . DOI
  5. Gerta Köster, Daniel Lehmberg, and Felix Dietrich: Is slowing down enough to model movement on stairs? Traffic and Granular Flow ’15, Springer International Publishing. DOI
  6. Daniel H. Biedermann, Felix Dietrich, Oliver Handel, Peter M. Kielar, and Michael Seitz: Using Raspberry Pi for scientific video observation of pedestrians during a music festival. Technical Report, Technische Universität München. Link to MediaTUM

2014

  1. Michael J. Seitz, Felix Dietrich, and Gerta Köster: A study of pedestrian stepping behaviour for crowd simulation. The Conference in Pedestrian and Evacuation Dynamics 2014, 282-290. DOI
  2. Felix Dietrich and Gerta Köster: Gradient navigation model for pedestrian dynamics. Physical Review E, 89, 062801. DOI, arXiv
  3. Felix Dietrich, Gerta Köster, Michael Seitz, and Isabella von Sivers: Bridging the gap: From cellular automata to differential equation models for pedestrian dynamics. Journal of Computational Science, 5, 841-846. DOI

2013

  1. Patrina A. Pellett, Felix Dietrich, Jörg Bewersdorf, James E Rothman, Grégory Lavieu: Inter-Golgi transport mediated by COPI-containing vesicles carrying small cargoes. eLife, eLife Sciences Publications, Ltd., 2, e01296-e01296. DOI