34 citations · 75 across the 7 of their papers we have counts for
9 papers
Reconstructing the information processing capacity of physical systems from noisy observations
Shun Kotoku, Rodrigo Martínez-Peña, Takatomo Mihana +5
Driven dynamical systems can compute when their transient states encode complex transformations of past inputs. The information processing capacity (IPC) framework allows for a det…
Data-Driven Acceleration of Multi-Physics Simulations
Stefan Meinecke, Malte Selig, Felix Köster +2
Multi-physics simulations play a crucial role in understanding complex systems. However, their computational demands are often prohibitive due to high dimensionality and complex in…
Data-Driven Forecasting of Non-Equilibrium Solid-State Dynamics
Stefan Meinecke, Felix Köster, Dominik Christiansen +3
We present a data-driven approach to efficiently approximate nonlinear transient dynamics in solid-state systems. Our proposed machine-learning model combines a dimensionality redu…
Attention-Enhanced Reservoir Computing
Felix Köster, Kazutaka Kanno, Jun Ohkubo +1
Photonic reservoir computing has been successfully utilized in time-series prediction as the need for hardware implementations has increased. Prediction of chaotic time series rema…
The role of delay-times in delay-based Photonic Reservoir Computing
Tobias Hülser, Felix Köster, Lina Jaurigue +1
Delay-based reservoir computing has gained a lot of attention due to the relative simplicity with which this concept can be implemented in hardware. However,there is still an misco…
Master memory function for delay-based reservoir computers with single-variable dynamics
Felix Köster, Serhiy Yanchuk, Kathy Lüdge
We show that many delay-based reservoir computers considered in the literature can be characterized by a universal master memory function (MMF). Once computed for two independent p…
Limitations of the recall capabilities in delay based reservoir computing systems
Felix Köster, Dominik Ehlert, Kathy Lüdge
We analyze the memory capacity of a delay based reservoir computer with a Hopf normal form as nonlinearity and numerically compute the linear as well as the higher order recall cap…
Insight into Delay Based Reservoir Computing via Eigenvalue Analysis
Felix Köster, Serhiy Yanchuk, Kathy Lüdge
In this paper we give a profound insight into the computation capability of delay-based reservoir computing via an eigenvalue analysis. We concentrate on the task-independent memor…
Deep Time-Delay Reservoir Computing: Dynamics and Memory Capacity
Mirko Goldmann, Felix Köster, Kathy Lüdge +1
The Deep Time-Delay Reservoir Computing concept utilizes unidirectionally connected systems with time-delays for supervised learning. We present how the dynamical properties of a d…