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	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
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	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	Nonparametric Statistics	On data-driven choice of 𝜆 in nonparametric Gaussian regression via Propagation–Separation approach	Computational Statistics & Data Analysis	Ewelina Fiebig
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
2019	Quantum Physics	Quantum rolling friction	Physical review letters	Francesco Intravaia, Marty Oelschläger, Daniel Reiche, Diego A. R. Dalvit, Kurt Busch
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	Statistical Physics	Variational approach to rare event simulation using least-squares regression	Chaos	Carsten Hartmann, Omar Kebiri, Lara Neureither, Lorenz Richter
2019	Applied Topology	The Conley index for discrete dynamical systems and the mapping torus	Journal of Applied and Computational Topology	Frank Weilandt
2019	Quantum Physics	Extended hydrodynamic description for nonequilibrium atom-surface interactions	JOSA B	Daniel Reiche, 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
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
2017	Theoretical Physics	Holograms of a Dynamical Top Quark	Physical Review D	William Clemens, Nick Evans, Marc Scott
2017	Algebraic Topology	Dimensional reduction and the equivariant Chern character	Algebraic and Geometric Topology	Augusto Stoffel
2017	Theoretical Physics	A Holographic Study of the Gauged NJL Model	Physical Letters B	William Clemens, Nick Evans
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	Nonlinear Dynamics	Onset of time dependence in ensembles of excitable elements with global repulsive coupling	Physical Review E	Michael A. Zaks, Petar Tomov
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
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