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Publications

dida regards itself as a company at the interface of scientific research and the practical application of Machine Learning, with scientists from well-known international research institutions.

Here we list academic papers that our Machine Learning Scientists have written or contributed to.

Year Research field Title Journal Authors
2020 Algebraic Topology A framework for geometric field theories and their classification in dimension one (submitted)

Matthias Ludewig, 

Augusto Stoffel
2020 Stochastic Processes Kernel autocovariance operators of stationary processes: Estimation and convergence (submitted)

Mattes Mollenhauer, 

Stefan Klus, 

Christof Schütte, 

Péter Koltai
2020 Nonparametric Statistics Kernel Conditional Density Operators AISTATS 2020

Ingmar Schuster, 

Mattes Mollenhauer, 

Stefan Klus, 

Krikamol Muandet
2020 Stochastic Processes Model Order Reduction for (Stochastic-) Delay Equations With Error Bounds (submitted)

Simon Becker, 

Lorenz Richter
2020 Nonparametric Statistics On data-driven choice of 𝜆 in nonparametric Gaussian regression via Propagation–Separation approach Computational Statistics & Data Analysis

Ewelina Fiebig
2020 Machine Learning Theory Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces Advances in Dynamics, Optimization and Computation (book chapter)

Mattes Mollenhauer, 

Ingmar Schuster, 

Stefan Klus, 

Christof Schütte
2020 Stochastic Processes, Optimal Control, Pdes Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space (submitted)

Nikolas Nüsken, 

Lorenz Richter
2020 Statistics, Machine Learning Theory VarGrad: A Low-Variance Gradient Estimator for Variational Inference Advances in Neural Information Processing Systems

Lorenz Richter, 

Ayman Boustati, 

Nikolas Nüsken, 

Francisco J. R. Ruiz, 

Ömer Deniz Akyildiz
2019 Quantum Physics Extended hydrodynamic description for nonequilibrium atom-surface interactions JOSA B

Daniel Reiche, 

Marty Oelschläger, 

Kurt Busch, 

Francesco Intravaia
2019 Stochastic Processes Feedback control theory & Model order reduction for stochastic equations (submitted)

Simon Becker, 

Carsten Hartmann, 

Martin Redmann, 

Lorenz Richter
2019 Nonlinear Dynamics, Machine Learning Theory Kernel methods for detecting coherent structures in dynamical data Chaos: An Interdisciplinary Journal of Nonlinear Science

Stefan Klus, 

Brooke E. Husic, 

Mattes Mollenhauer, 

Frank Noé
2019 Quantum Physics Quantum rolling friction Physical review letters

Francesco Intravaia, 

Marty Oelschläger, 

Daniel Reiche, 

Diego A. R. Dalvit, 

Kurt Busch
2019 Applied Topology The Conley index for discrete dynamical systems and the mapping torus Journal of Applied and Computational Topology

Frank Weilandt
2019 Statistical Physics Variational approach to rare event simulation using least-squares regression Chaos

Carsten Hartmann, 

Omar Kebiri, 

Lara Neureither, 

Lorenz Richter
2018 Theoretical Physics Holographic Gauged NJL Model: the Conformal Window and Ideal Walking Physical Review D

Kazem Bitaghsir Fadafan, 

William Clemens, 

Nick Evans
2018 Quantum Physics Nonequilibrium atom-surface interaction with lossy multilayer structures Physical Review A

Marty Oelschläger, 

Kurt Busch, 

Francesco Intravaia
2018 Algebraic Topology Supersymmetric field theories from twisted vector bundles Communications in Mathematical Physics

Augusto Stoffel
2018 Algebraic Geometry, High Energy Physics Toric geometry and regularization of Feynman integrals (unpublished)

Konrad Schultka
2017 Theoretical Physics A Holographic Study of the Gauged NJL Model Physical Letters B

William Clemens, 

Nick Evans
2017 Algebraic Topology Dimensional reduction and the equivariant Chern character Algebraic and Geometric Topology

Augusto Stoffel
2017 Theoretical Physics Holograms of a Dynamical Top Quark Physical Review D

William Clemens, 

Nick Evans, 

Marc Scott
2017 Statistical Physics Variational characterization of free energy: Theory and algorithms Entropy

Carsten Hartmann, 

Lorenz Richter, 

Christof Schütte, 

Wei Zhang
2016 Computational Dynamical Systems Discretization strategies for computing Conley indices and Morse decompositions of flows Journal of Computational Dynamics

Konstantin Mischaikow, 

Marian Mrozek, 

Frank Weilandt
2016 Computational Neuroscience Mechanisms of self-sustained oscillatory states in hierarchical modular networks with mixtures of electrophysiological cell types Frontiers in Computational Neuroscience

Petar Tomov, 

Rodrigo F. O. Pena, 

Antonio C. Roque, 

Michael A. Zaks
2016 Nonlinear Dynamics Onset of time dependence in ensembles of excitable elements with global repulsive coupling Physical Review E

Michael A. Zaks, 

Petar Tomov
2015 Computational Dynamical Systems A topological approach to the algorithmic computation of the Conley index for Poincaré maps SIAM Journal on Applied Dynamical Systems

Marian Mrozek, 

Roman Srzednicki, 

Frank Weilandt
2014 Computational Neuroscience Sustained oscillations, irregular firing, and chaotic dynamics in hierarchical modular networks with mixtures of electrophysiological cell types Frontiers in Computational Neuroscience

Petar Tomov, 

Rodrigo F. O. Pena, 

Michael A. Zaks, 

Antonio C. Roque