Search Results for author: André Röhm

Found 7 papers, 1 papers with code

Conflict-free joint sampling for preference satisfaction through quantum interference

no code implementations5 Aug 2022 Hiroaki Shinkawa, Nicolas Chauvet, André Röhm, Takatomo Mihana, Ryoichi Horisaki, Guillaume Bachelier, Makoto Naruse

First, as the number of choices increases, the computational cost of calculating the optimal joint selection probability matrix explodes.

Decision Making

Learning unseen coexisting attractors

no code implementations28 Jul 2022 Daniel J. Gauthier, Ingo Fischer, André Röhm

Reservoir computing is a machine learning approach that can generate a surrogate model of a dynamical system.

BIG-bench Machine Learning

Optimal preference satisfaction for conflict-free joint decisions

no code implementations2 May 2022 Hiroaki Shinkawa, Nicolas Chauvet, Guillaume Bachelier, André Röhm, Ryoichi Horisaki, Makoto Naruse

Here, we theoretically derive conflict-free joint decision-making that can satisfy the probabilistic preferences of all individual players.

Decision Making

Deep Neural Networks using a Single Neuron: Folded-in-Time Architecture using Feedback-Modulated Delay Loops

1 code implementation19 Nov 2020 Florian Stelzer, André Röhm, Raul Vicente, Ingo Fischer, Serhiy Yanchuk

We present a method for folding a deep neural network of arbitrary size into a single neuron with multiple time-delayed feedback loops.

Performance boost of time-delay reservoir computing by non-resonant clock cycle

no code implementations7 May 2019 Florian Stelzer, André Röhm, Kathy Lüdge, Serhiy Yanchuk

Here we show that the case of equal or resonant time-delay and clock cycle could be actively detrimental and leads to an increase of the approximation error of the reservoir.

Reservoir computing with simple oscillators: Virtual and real networks

no code implementations23 Feb 2018 André Röhm, Kathy Lüdge

The reservoir computing scheme is a machine learning mechanism which utilizes the naturally occuring computational capabilities of dynamical systems.

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