Felix Dietrich

Orcid: 0000-0002-2906-1769

Affiliations:
  • Technical University of Munich, Department of Informatics, Germany
  • Johns Hopkins University, Department of Chemical and Biomolecular Engineering, Baltimore, MD, USA


According to our database1, Felix Dietrich authored at least 39 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms.
SIAM J. Sci. Comput., 2024

Multi-fidelity Gaussian process surrogate modeling for regression problems in physics.
Mach. Learn. Sci. Technol., 2024

Gradient-free training of recurrent neural networks.
CoRR, 2024

Accelerating Full Waveform Inversion By Transfer Learning.
CoRR, 2024

On Learning what to Learn: heterogeneous observations of dynamics and establishing (possibly causal) relations among them.
CoRR, 2024

Solving partial differential equations with sampled neural networks.
CoRR, 2024

Systematic construction of continuous-time neural networks for linear dynamical systems.
CoRR, 2024

2023
NOMAD: A distributed web-based platform for managing materials science research data.
J. Open Source Softw., October, 2023

Quantum process tomography of unitary maps from time-delayed measurements.
Quantum Inf. Process., 2023

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space.
J. Comput. Phys., 2023

Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity.
CoRR, 2023

Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator.
CoRR, 2023

On the Use of Neural Networks for Full Waveform Inversion.
CoRR, 2023

Sampling weights of deep neural networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FAIR Research Data With NOMAD FAIRmat's Distributed, Schema-based Research-data Infrastructure to Harmonize RDM in Materials Science.
Proceedings of the 1st Conference on Research Data Infrastructure - Connecting Communities, 2023

2022
Spectral Discovery of Jointly Smooth Features for Multimodal Data.
SIAM J. Math. Data Sci., 2022

Personalized Algorithm Generation: A Case Study in Learning ODE Integrators.
SIAM J. Sci. Comput., 2022

Learning Effective SDEs from Brownian Dynamics Simulations of Colloidal Particles.
CoRR, 2022

Safe Policy Improvement Approaches and Their Limitations.
Proceedings of the Agents and Artificial Intelligence - 14th International Conference, 2022

Safe Policy Improvement Approaches on Discrete Markov Decision Processes.
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021
On the Parameter Combinations That Matter and on Those That do Not.
CoRR, 2021

On the Correspondence between Gaussian Processes and Geometric Harmonics.
CoRR, 2021

Learning the temporal evolution of multivariate densities via normalizing flows.
CoRR, 2021

Learning effective stochastic differential equations from microscopic simulations: combining stochastic numerics and deep learning.
CoRR, 2021

Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators.
CoRR, 2021

2020
On the Koopman Operator of Algorithms.
SIAM J. Appl. Dyn. Syst., 2020

A Geometric Approach to the Transport of Discontinuous Densities.
SIAM/ASA J. Uncertain. Quantification, 2020

datafold: data-driven models for point clouds and time series on manifolds.
J. Open Source Softw., 2020

Learning emergent PDEs in a learned emergent space.
CoRR, 2020

Transformations between deep neural networks.
CoRR, 2020

LOCA: LOcal Conformal Autoencoder for standardized data coordinates.
CoRR, 2020

2019
Optimal Transport on the Manifold of SPD Matrices for Domain Adaptation.
CoRR, 2019

FFT-Based Solution Schemes for the Unit Cell Problem in Periodic Homogenization of Magneto-Elastic Coupling.
Proceedings of the Numerical Mathematics and Advanced Applications ENUMATH 2019 - European Conference, Egmond aan Zee, The Netherlands, September 30, 2019

2018
On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions.
SIAM J. Appl. Dyn. Syst., 2018

Linking Gaussian Process regression with data-driven manifold embeddings for nonlinear data fusion.
CoRR, 2018

An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning.
IEEE Access, 2018

2016
Numerical Model Construction with Closed Observables.
SIAM J. Appl. Dyn. Syst., 2016

2015
Using Raspberry Pi for scientific video observation of pedestrians during a music festival.
CoRR, 2015

2014
Bridging the gap: From cellular automata to differential equation models for pedestrian dynamics.
J. Comput. Sci., 2014


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