Reservoir computing with simple oscillators: Virtual and real networks. - André Röhm; Kathy Lüdge (CoRR, 2018)

Computing with a camera. - Kathy Lüdge; André Röhm (Nat. Mach. Intell., 2019)

Deep Learning with a Single Neuron: Folding a Deep Neural Network in Time using Feedback-Modulated Delay Loops. - Florian Stelzer; André Röhm; Raul Vicente; Ingo Fischer; Serhiy Yanchuk (CoRR, 2020)

Performance boost of time-delay reservoir computing by non-resonant clock cycle. - Florian Stelzer; André Röhm; Kathy Lüdge; Serhiy Yanchuk (Neural Networks, 2020)

Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing. - André Röhm; Daniel J. Gauthier; Ingo Fischer (CoRR, 2021)

Efficient Pairing in Unknown Environments: Minimal Observations and TSP-Based Optimization. - Naoki Fujita; Nicolas Chauvet; André Röhm; Ryoichi Horisaki; Aohan Li; Mikio Hasegawa; Makoto Naruse (IEEE Access, 2022)

Directivity of Quantum Walk via Its Random Walk Replica. - Tomoki Yamagami; Etsuo Segawa; Nicolas Chauvet; André Röhm; Ryoichi Horisaki; Makoto Naruse (Complex., 2022)

Learning unseen coexisting attractors. - Daniel J. Gauthier; Ingo Fischer; André Röhm (CoRR, 2022)

Conflict-free joint sampling for preference satisfaction through quantum interference. - Hiroaki Shinkawa; Nicolas Chauvet; André Röhm; Takatomo Mihana; Ryoichi Horisaki; Guillaume Bachelier; Makoto Naruse (CoRR, 2022)

Skeleton structure inherent in discrete-time quantum walks. - Tomoki Yamagami; Etsuo Segawa; Ken'ichiro Tanaka; Takatomo Mihana; André Röhm; Ryoichi Horisaki; Makoto Naruse (CoRR, 2022)

Bandit approach to conflict-free multi-agent Q-learning in view of photonic implementation. - Hiroaki Shinkawa; Nicolas Chauvet; André Röhm; Takatomo Mihana; Ryoichi Horisaki; Guillaume Bachelier; Makoto Naruse (CoRR, 2022)

Information Processing Capacity of a Single-Node Reservoir Computer: An Experimental Evaluation. - Benedikt Vettelschoss; André Röhm; Miguel C. Soriano (IEEE Trans. Neural Networks Learn. Syst., 2022)

Optimal Preference Satisfaction for Conflict-Free Joint Decisions. - Hiroaki Shinkawa; Nicolas Chauvet; Guillaume Bachelier; André Röhm; Ryoichi Horisaki; Makoto Naruse (Complex., 2023)

Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computing. - Kohei Tsuchiyama; André Röhm; Takatomo Mihana; Ryoichi Horisaki; Makoto Naruse (CoRR, 2023)

Asymmetric quantum decision-making. - Honoka Shiratori; Hiroaki Shinkawa; André Röhm; Nicolas Chauvet; Etsuo Segawa; Jonathan Laurent; Guillaume Bachelier; Tomoki Yamagami; Ryoichi Horisaki; Makoto Naruse (CoRR, 2023)

Asymmetric leader-laggard cluster synchronization for collective decision-making with laser network. - Shun Kotoku; Takatomo Mihana; André Röhm; Ryoichi Horisaki; Makoto Naruse (CoRR, 2023)

Pairing Optimization via Statistics: Algebraic Structure in Pairing Problems and Its Application to Performance Enhancement. - Naoki Fujita; André Röhm; Takatomo Mihana; Ryoichi Horisaki; Aohan Li; Mikio Hasegawa; Makoto Naruse (Entropy, 2023)

Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk. - Tomoki Yamagami; Etsuo Segawa; Takatomo Mihana; André Röhm; Ryoichi Horisaki; Makoto Naruse (Entropy, 2023)

Acceleration of Approximate Matrix Multiplications on GPUs. - Takuya Okuyama; André Röhm; Takatomo Mihana; Makoto Naruse (Entropy, 2023)

Decentralized multi-agent reinforcement learning algorithm using a cluster-synchronized laser network. - Shun Kotoku; Takatomo Mihana; André Röhm; Ryoichi Horisaki (CoRR, 2024)

Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks. - Satoshi Sunada; Tomoaki Niiyama; Kazutaka Kanno; Rin Nogami; André Röhm; Takato Awano; Atsushi Uchida (CoRR, 2025)