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Training Hamiltonian neural networks without backpropagation
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2024
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Abdul Monem S. Rahma
Chinmay Datar
Felix Dietrich
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Gradient-free training of recurrent neural networks
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2024
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Erik Lien Bolager
Ana Cukarska
Iryna Burak
Zahra Monfared
Felix Dietrich
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Multi-fidelity Gaussian process surrogate modeling for regression problems in physics
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2024
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Kislaya Ravi
Vladyslav Fediukov
Felix Dietrich
Tobias Neckel
Fabian Buse
M. Bergmann
HansâJoachim Bungartz
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Accelerating Full Waveform Inversion By Transfer Learning
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2024
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Divya Shyam Singh
Leon Herrmann
Qiang Sun
Tim BĂŒrchner
Felix Dietrich
Stefan Kollmannsberger
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On Learning what to Learn: heterogeneous observations of dynamics and
establishing (possibly causal) relations among them
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2024
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David W. Sroczynski
Felix Dietrich
Eleni D. Koronaki
Ronen Talmon
Ronald R. Coifman
Erik M. Bollt
Ioannis G. Kevrekidis
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Solving partial differential equations with sampled neural networks
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2024
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Chinmay Datar
Taniya Kapoor
Abhishek Chandra
Qing Sun
Iryna Burak
Erik Lien Bolager
Anna Veselovska
Massimo Fornasier
Felix Dietrich
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Multi-fidelity Gaussian process surrogate modeling for regression
problems in physics
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2024
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Kislaya Ravi
Vladyslav Fediukov
Felix Dietrich
Tobias Neckel
Fabian Buse
Michael Bergmann
HansâJoachim Bungartz
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Systematic construction of continuous-time neural networks for linear
dynamical systems
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2024
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Chinmay Datar
Adwait Datar
Felix Dietrich
W.H.A. Schilders
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A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
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2024
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Danimir T. Doncevic
Alexander Mitsos
Y. P. Guo
Qianxiao Li
Felix Dietrich
Manuel Dahmen
Ioannis G. Kevrekidis
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Data-driven modelling of brain activity using neural networks, diffusion maps, and the Koopman operator
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2024
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Ioannis Gallos
Daniel Lehmberg
Felix Dietrich
Constantinos Siettos
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On the use of neural networks for full waveform inversion
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2023
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Leon Herrmann
Tim BĂŒrchner
Felix Dietrich
Stefan Kollmannsberger
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Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space
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2023
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Nikolaos Evangelou
Felix Dietrich
Eliodoro Chiavazzo
Daniel Lehmberg
Marina MeilÄ
Ioannis G. Kevrekidis
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Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning
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2023
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Felix Dietrich
Alexei G. Makeev
George A. Kevrekidis
Nikolaos Evangelou
Tom Bertalan
Sebastian Reich
Ioannis G. Kevrekidis
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On the Use of Neural Networks for Full Waveform Inversion
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2023
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Leon Herrmann
Tim BĂŒrchner
Felix Dietrich
Stefan Kollmannsberger
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Learning effective SDEs from Brownian dynamic simulations of colloidal particles
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2023
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Nikolaos Evangelou
Felix Dietrich
Juan M. BelloâRivas
Alex Yeh
Rachel S. Hendley
Michael A. Bevan
I.G. Kevrekidis
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Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator
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2023
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Ioannis Gallos
Daniel Lehmberg
Felix Dietrich
Constantinos Siettos
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Transporting Densities Across Dimensions
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2023
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Michael Plainer
Felix Dietrich
Ioannis G. Kevrekidis
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Sampling weights of deep neural networks
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2023
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Erik Lien Bolager
Iryna Burak
Chinmay Datar
Qing Sun
Felix Dietrich
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Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity
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2023
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Erez Peterfreund
Iryna Burak
Ofir Lindenbaum
Jim Gimlett
Felix Dietrich
Ronald R. Coifman
Ioannis G. Kevrekidis
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Personalized Algorithm Generation: A Case Study in Learning ODE Integrators
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2022
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Y. P. Guo
Felix Dietrich
Tom Bertalan
Danimir T. Doncevic
Manuel Dahmen
Ioannis G. Kevrekidis
Qianxiao Li
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Spectral Discovery of Jointly Smooth Features for Multimodal Data
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2022
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Felix Dietrich
Or Yair
Rotem Mulayoff
Ronen Talmon
Ioannis G. Kevrekidis
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Learning the temporal evolution of multivariate densities via normalizing flows
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2022
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Yubin Lu
Romit Maulik
Ting Gao
Felix Dietrich
Ioannis G. Kevrekidis
Jinqiao Duan
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Safe Policy Improvement Approaches on Discrete Markov Decision Processes
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2022
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Philipp Scholl
Felix Dietrich
Clemens Otte
Steffen Udluft
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Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space
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2022
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Nikos Evangelou
Felix Dietrich
Eliodoro Chiavazzo
Daniel Lehmberg
Marina MeilÄ
Ioannis G. Kevrekidis
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Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles
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2022
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Nikos Evangelou
Felix Dietrich
Juan M. BelloâRivas
Alex Yeh
Rachel Stein
Michael A. Bevan
Ioannis G. Kevekidis
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Safe Policy Improvement Approaches on Discrete Markov Decision Processes
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2022
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Philipp M. Scholl
Felix Dietrich
Clemens Otte
Steffen Udluft
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Safe Policy Improvement Approaches and their Limitations
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2022
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Philipp M. Scholl
Felix Dietrich
Clemens Otte
Steffen Udluft
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A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
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2022
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Danimir T. Doncevic
Alexander Mitsos
Yue Guo
Qianxiao Li
Felix Dietrich
Manuel Dahmen
Ioannis G. Kevrekidis
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Safe Policy Improvement Approaches and Their Limitations
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2022
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Philipp Scholl
Felix Dietrich
Clemens Otte
Steffen Udluft
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Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning.
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2021
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Felix Dietrich
Alexei G. Makeev
George A. Kevrekidis
Nikolaos Evangelou
Tom Bertalan
Sebastian Reich
Ioannis G. Kevrekidis
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Learning effective stochastic differential equations from microscopic
simulations: combining stochastic numerics and deep learning
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2021
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Felix Dietrich
Alexei G. Makeev
George A. Kevrekidis
Nikos Evangelou
Tom Bertalan
Stephanie Reich
Ioannis G. Kevrekidis
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Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators.
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2021
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Y. P. Guo
Felix Dietrich
Tom Bertalan
Danimir T. Doncevic
Manuel Dahmen
Ioannis G. Kevrekidis
Qianxiao Li
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On the Correspondence between Gaussian Processes and Geometric Harmonics
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2021
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Felix Dietrich
Juan M. BelloâRivas
Ioannis G. Kevrekidis
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Quantum Process Tomography of Unitary Maps from Time-Delayed Measurements
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2021
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Irene López Gutiérrez
Felix Dietrich
Christian B. Mendl
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On the Parameter Combinations That Matter and on Those That do Not
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2021
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Nikos Evangelou
Noah J. Wichrowski
George A. Kevrekidis
Felix Dietrich
Mahdi Kooshkbaghi
Sarah McFann
Ioannis G. Kevrekidis
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Learning effective stochastic differential equations from microscopic simulations: linking stochastic numerics to deep learning
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2021
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Felix Dietrich
Alexei G. Makeev
George A. Kevrekidis
Nikos Evangelou
Tom Bertalan
Stephanie Reich
Ioannis G. Kevrekidis
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Local conformal autoencoder for standardized data coordinates
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2020
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Erez Peterfreund
Ofir Lindenbaum
Felix Dietrich
Tom Bertalan
Matan Gavish
Ioannis G. Kevrekidis
Ronald R. Coifman
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Geometric necks in mean curvature flow of 2-convex hypersurfaces
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2020
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Felix Dietrich
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LOCA: LOcal Conformal Autoencoder for standardized data coordinates
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2020
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Erez Peterfreund
Ofir Lindenbaum
Felix Dietrich
Tom Bertalan
Matan Gavish
Ioannis G. Kevrekidis
Ronald R. Coifman
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Manifold learning for organizing unstructured sets of process observations
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2020
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Felix Dietrich
Mahdi Kooshkbaghi
Erik M. Bollt
Ioannis G. Kevrekidis
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On the Koopman Operator of Algorithms
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2020
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Felix Dietrich
Thomas N. Thiem
Ioannis G. Kevrekidis
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A Geometric Approach to the Transport of Discontinuous Densities
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2020
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Caroline MoosmĂŒller
Felix Dietrich
Ioannis G. Kevrekidis
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Transformations between deep neural networks
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2020
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Tom Bertalan
Felix Dietrich
Ioannis G. Kevrekidis
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Learning emergent PDEs in a learned emergent space
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2020
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Felix P. Kemeth
Tom Bertalan
Thomas N. Thiem
Felix Dietrich
Sung Joon Moon
Carlo R. Laing
Ioannis G. Kevrekidis
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On learning Hamiltonian systems from data
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2019
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Tom Bertalan
Felix Dietrich
Igor MeziÄ
Ioannis G. Kevrekidis
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Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation
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2019
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Or Yair
Felix Dietrich
Ronen Talmon
Ioannis G. Kevrekidis
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Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
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2019
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Or Yair
Felix Dietrich
Ronen Talmon
Ioannis G. Kevrekidis
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Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion
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2019
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SeungâJoon Lee
Felix Dietrich
George Em Karniadakis
Ioannis G. Kevrekidis
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Status of the undulator-based ILC positron source
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2019
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Felix Dietrich
Gudrid MoortgatâPick
Sabine Riemann
P. Sievers
Andriy Ushakov
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Derivation of Higher-Order Terms in FFT-Based Numerical Homogenization
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2019
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Felix Dietrich
Dennis Merkert
Bernd Simeon
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A geometric approach to the transport of discontinuous densities
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2019
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Caroline MoosmĂŒller
Felix Dietrich
Ioannis G. Kevrekidis
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Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
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2019
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Or Yair
Felix Dietrich
Ronen Talmon
Ioannis G. Kevrekidis
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Manifold Learning for Bifurcation Diagram Observations
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2018
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Felix Dietrich
Mahdi Kooshkbaghi
Erik M. Bollt
Ioannis G. Kevrekidis
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The ILC positron target cooled by thermal radiation
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2018
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Sabine Riemann
Felix Dietrich
Andriy Ushakov
P. Sievers
Gudrid MoortgatâPick
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FAST AND FLEXIBLE UNCERTAINTY QUANTIFICATION THROUGH A DATA-DRIVEN SURROGATE MODEL
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2018
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Felix Dietrich
Florian KĂŒnzner
Tobias Neckel
Gerta Köster
HansâJoachim Bungartz
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An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning
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2018
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Felix P. Kemeth
Sindre W. Haugland
Felix Dietrich
Tom Bertalan
Kevin Höhlein
Qianxiao Li
Erik M. Bollt
Ronen Talmon
Katharina Krischer
Ioannis G. Kevrekidis
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On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions
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2018
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Erik M. Bollt
Qianxiao Li
Felix Dietrich
Ioannis G. Kevrekidis
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Some manifold learning considerations towards explicit model predictive control
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2018
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Robert J. Lovelett
Felix Dietrich
Seungjoon Lee
Ioannis G. Kevrekidis
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On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions
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2017
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Erik M. Bollt
Qianxiao Li
Felix Dietrich
Ioannis G. Kevrekidis
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Derivation of higher-order terms in FFT-based numerical homogenization
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2017
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Felix Dietrich
Dennis Merkert
Bernd Simeon
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Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
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2017
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Qianxiao Li
Felix Dietrich
Erik M. Bollt
Ioannis G. Kevrekidis
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An Equal Space for Complex Data with Unknown Internal Order: Observability, Gauge Invariance and Manifold Learning
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2017
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Felix P. Kemeth
Sindre W. Haugland
Felix Dietrich
Tom Bertalan
Qianxiao Li
Erik M. Bollt
Ronen Talmon
Katharina Krischer
Ioannis G. Kevrekidis
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Data-Driven Surrogate Models for Dynamical Systems
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2017
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Felix Dietrich
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On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions
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2017
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Erik M. Bollt
Qianxiao Li
Felix Dietrich
Ioannis G. Kevrekidis
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Derivation of higher-order terms in FFT-based numerical homogenization
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2017
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Felix Dietrich
Dennis Merkert
Bernd Simeon
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Numerical Model Construction with Closed Observables
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2016
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Felix Dietrich
Gerta Köster
HansâJoachim Bungartz
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Using Raspberry Pi for scientific video observation of pedestrians during a music festival
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2015
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Daniel H. Biedermann
Felix Dietrich
Oliver Handel
Peter M. Kielar
Michael Seitz
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Gradient navigation model for pedestrian dynamics
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2014
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Felix Dietrich
Gerta Köster
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