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2020 – today
- 2024
[i12]Guillaume Pourcel, Mirko Goldmann, Ingo Fischer, Miguel C. Soriano:
Adaptive control of recurrent neural networks using conceptors. CoRR abs/2405.07236 (2024)- [i11]Moritz Pflüger, Daniel Brunner, Tobias Heuser, James A. Lott, Stephan Reitzenstein, Ingo Fischer:
Experimental reservoir computing with diffractively coupled VCSELs. CoRR abs/2412.03206 (2024) - 2022
- [i10]Daniel J. Gauthier, Ingo Fischer, André Röhm:
Learning unseen coexisting attractors. CoRR abs/2207.14133 (2022) - 2021
- [j8]Daniel J. Gauthier
, Ingo Fischer:
Predicting hidden structure in dynamical systems. Nat. Mach. Intell. 3(4): 281-282 (2021) - [j7]Aref Pariz, Ingo Fischer, Alireza Valizadeh, Claudio R. Mirasso:
Transmission delays and frequency detuning can regulate information flow between brain regions. PLoS Comput. Biol. 17(4) (2021) - [c6]Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer, Miguel C. Soriano:
Exploiting transient dynamics of a time-multiplexed reservoir to boost the system performance. IJCNN 2021: 1-8 - [e1]Kohei Nakajima, Ingo Fischer:
Reservoir Computing - Theory, Physical Implementations, and Applications. Natural Computing Series, Springer 2021, ISBN 978-981-13-1686-9 [contents] - [i9]André Röhm, Daniel J. Gauthier, Ingo Fischer:
Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing. CoRR abs/2108.04074 (2021) - [i8]Daniel Brunner, Bogdan Penkovsky, Bicky A. Marquez, M. Jaquot, Ingo Fischer, Laurent Larger:
Tutorial: Photonic Neural Networks in Delay Systems. CoRR abs/2111.03332 (2021) - [i7]Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer, Miguel C. Soriano:
Inferring untrained complex dynamics of delay systems using an adapted echo state network. CoRR abs/2111.03706 (2021) - 2020
- [c5]Irene Estébanez, Janek Schwind, Ingo Fischer, Apostolos Argyris:
Bandwidth Enhanced Operation of Photonic Time Delay Reservoir Computing. ECOC 2020: 1-4 - [i6]Tobias Heuser, Moritz Pflüger, Ingo Fischer, James A. Lott, Daniel Brunner, Stephan Reitzenstein:
Developing of a photonic hardware platform for brain-inspired computing based on 5×5 VCSEL arrays. CoRR abs/2006.13933 (2020) - [i5]Florian Stelzer, André Röhm, Raul Vicente, Ingo Fischer, Serhiy Yanchuk:
Deep Learning with a Single Neuron: Folding a Deep Neural Network in Time using Feedback-Modulated Delay Loops. CoRR abs/2011.10115 (2020)
2010 – 2019
- 2019
- [j6]Apostolos Argyris, Julian Bueno, Ingo Fischer:
PAM-4 Transmission at 1550 nm Using Photonic Reservoir Computing Post-Processing. IEEE Access 7: 37017-37025 (2019) - [c4]Miguel C. Soriano, Pau Massuti-Ballester, Jesús Yelo, Ingo Fischer:
Optoelectronic Reservoir Computing Using a Mixed Digital-Analog Hardware Implementation. ICANN (Workshop) 2019: 170-174 - 2017
- [c3]Apostolos Argyris, Julian Bueno, Ingo Fischer:
Post-processing of Long-haul and Ethernet Optical Transmission Signals Using Photonic Reservoir Computing. ECOC 2017: 1-3 - [i4]Julian Bueno, Sheler Maktoobi, Luc Froehly, Ingo Fischer, Maxime Jacquot, Laurent Larger, Daniel Brunner:
Reinforcement Learning in a large scale photonic Recurrent Neural Network. CoRR abs/1711.05133 (2017) - 2016
- [j5]Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek, Dragana Bajovic, Dino Sejdinovic, Günes Karabulut-Kurt, Camilla Hollanti, Ingo Fischer:
CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT. IEEE Access 4: 3360-3378 (2016) - [c2]Daniel Brunner, Stephan Reitzenstein, Ingo Fischer:
All-optical neuromorphic computing in optical networks of semiconductor lasers. ICRC 2016: 1-2 - [i3]Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek, Dragana Bajovic, Dino Sejdinovic, Gunes Karabulut-Kurt, Camilla Hollanti, Ingo Fischer:
CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT. CoRR abs/1609.03363 (2016) - 2015
- [j4]Miguel C. Soriano, Daniel Brunner, Miguel Angel Escalona-Moran, Claudio R. Mirasso, Ingo Fischer:
Minimal approach to neuro-inspired information processing. Frontiers Comput. Neurosci. 9: 68 (2015) - [j3]Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer:
Photonic delay systems as machine learning implementations. J. Mach. Learn. Res. 16: 2081-2097 (2015) - [j2]Miquel L. Alomar, Miguel C. Soriano, Miguel Angel Escalona-Moran, Vincent Canals, Ingo Fischer, Claudio R. Mirasso, José Luis Rosselló:
Digital Implementation of a Single Dynamical Node Reservoir Computer. IEEE Trans. Circuits Syst. II Express Briefs 62-II(10): 977-981 (2015) - [j1]Miguel Angel Escalona-Moran, Miguel C. Soriano, Ingo Fischer, Claudio R. Mirasso:
Electrocardiogram Classification Using Reservoir Computing With Logistic Regression. IEEE J. Biomed. Health Informatics 19(3): 892-898 (2015) - [i2]Michiel Hermans, Miguel C. Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer:
Photonic Delay Systems as Machine Learning Implementations. CoRR abs/1501.02592 (2015) - 2014
- [i1]Nicholas D. Haynes, Miguel C. Soriano, Ingo Fischer, Daniel J. Gauthier:
Reservoir computing with a single time-delay autonomous Boolean node. CoRR abs/1411.1398 (2014)
2000 – 2009
- 2007
- [c1]Raul Vicente, Gordon Pipa, Ingo Fischer, Claudio R. Mirasso:
Zero-Lag Long Range Synchronization of Neurons Is Enhanced by Dynamical Relaying. ICANN (1) 2007: 904-913
Coauthor Index
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