Michiel Hermans

1.2k total citations
21 papers, 758 citations indexed

About

Michiel Hermans is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Cognitive Neuroscience. According to data from OpenAlex, Michiel Hermans has authored 21 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 14 papers in Electrical and Electronic Engineering and 5 papers in Cognitive Neuroscience. Recurrent topics in Michiel Hermans's work include Neural Networks and Reservoir Computing (15 papers), Advanced Memory and Neural Computing (14 papers) and Optical Network Technologies (7 papers). Michiel Hermans is often cited by papers focused on Neural Networks and Reservoir Computing (15 papers), Advanced Memory and Neural Computing (14 papers) and Optical Network Technologies (7 papers). Michiel Hermans collaborates with scholars based in Belgium, Spain and France. Michiel Hermans's co-authors include Benjamin Schrauwen, Joni Dambre, Francis wyffels, Peter Bienstman, Jonas Degrave, Marc Haelterman, Serge Massar, Piotr Antonik, François Duport and Thomas Van Vaerenbergh and has published in prestigious journals such as Physical Review Letters, Nature Communications and PLoS ONE.

In The Last Decade

Michiel Hermans

21 papers receiving 718 citations

Peers

Michiel Hermans

EEE

CVPR

CSE

Boudour Ammar Tunisia

Dan Hammerstrom United States

Karim Mohammadi Iran

Boyu Wang China

Xing Wang China

Vicente Alarcon‐Aquino Mexico

Vincent Gripon France

Mustafa Poyraz Türkiye

Fatemeh Daneshfar Iran

Fernando Gama United States

Boudour Ammar Tunisia

Michiel Hermans

287 ×0.6

172 ×0.6

EEE

48 ×0.5

51 ×0.6

CVPR

72 ×1.0

CSE

Citations per year, relative to Michiel Hermans Michiel Hermans (= 1×) peers Boudour Ammar

Countries citing papers authored by Michiel Hermans

Since Specialization

Citations

This map shows the geographic impact of Michiel Hermans's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michiel Hermans with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michiel Hermans more than expected).

Fields of papers citing papers by Michiel Hermans

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michiel Hermans. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michiel Hermans. The network helps show where Michiel Hermans may publish in the future.

Co-authorship network of co-authors of Michiel Hermans

This figure shows the co-authorship network connecting the top 25 collaborators of Michiel Hermans. A scholar is included among the top collaborators of Michiel Hermans based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michiel Hermans. Michiel Hermans is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Degrave, Jonas, Michiel Hermans, Joni Dambre, & Francis wyffels. (2019). A Differentiable Physics Engine for Deep Learning in Robotics. Frontiers in Neurorobotics. 13. 6–6. 95 indexed citations

Antonik, Piotr, Michiel Hermans, Marc Haelterman, & Serge Massar. (2017). Random Pattern and Frequency Generation Using a Photonic Reservoir Computer with Output Feedback. Neural Processing Letters. 47(3). 1041–1054. 2 indexed citations

Antonik, Piotr, Michiel Hermans, Marc Haelterman, & Serge Massar. (2017). Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 2 indexed citations

Antonik, Piotr, Michiel Hermans, Marc Haelterman, & Serge Massar. (2017). Photonic reservoir computer with output feedback for chaotic time series prediction. 9732. 2407–2413. 1 indexed citations

Hermans, Michiel, Piotr Antonik, Marc Haelterman, & Serge Massar. (2016). Embodiment of Learning in Electro-Optical Signal Processors. Physical Review Letters. 117(12). 128301–128301. 29 indexed citations

Degrave, Jonas, Michiel Hermans, Joni Dambre, & Francis wyffels. (2016). A Differentiable Physics Engine for Deep Learning in Robotics. arXiv (Cornell University). 1 indexed citations

Antonik, Piotr, François Duport, Michiel Hermans, et al.. (2016). Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalization. IEEE Transactions on Neural Networks and Learning Systems. 28(11). 2686–2698. 58 indexed citations

Hermans, Michiel, et al.. (2015). Trainable hardware for dynamical computing using error backpropagation through physical media. Nature Communications. 6(1). 6729–6729. 48 indexed citations

Hermans, Michiel, Miguel C. Soriano, Joni Dambre, Peter Bienstman, & Ingo Fischer. (2015). Photonic Delay Systems as Machine Learning Implementations. arXiv (Cornell University). 16(1). 2081–2097. 29 indexed citations

10.

Hermans, Michiel, Benjamin Schrauwen, Peter Bienstman, & Joni Dambre. (2014). Automated Design of Complex Dynamic Systems. PLoS ONE. 9(1). e86696–e86696. 15 indexed citations

11.

Hermans, Michiel, Joni Dambre, & Peter Bienstman. (2014). Optoelectronic Systems Trained With Backpropagation Through Time. IEEE Transactions on Neural Networks and Learning Systems. 26(7). 1545–1550. 18 indexed citations

12.

Hermans, Michiel & Benjamin Schrauwen. (2013). Training and Analysing Deep Recurrent Neural Networks. Neural Information Processing Systems. 26. 190–198. 256 indexed citations

13.

Hermans, Michiel & Benjamin Schrauwen. (2013). Training and analyzing deep recurrent neural networks. Neural Information Processing Systems. 190–198. 63 indexed citations

14.

Hermans, Michiel, et al.. (2013). MACOP modular architecture with control primitives. Frontiers in Computational Neuroscience. 7. 99–99. 9 indexed citations

15.

Hermans, Michiel & Benjamin Schrauwen. (2011). Recurrent Kernel Machines: Computing with Infinite Echo State Networks. Neural Computation. 24(1). 104–133. 54 indexed citations

16.

wyffels, Francis, Michiel Hermans, & Benjamin Schrauwen. (2010). Building robots as a tool to motivate students into an engineering education. Ghent University Academic Bibliography (Ghent University). 49–52. 6 indexed citations

17.

Hermans, Michiel & Benjamin Schrauwen. (2010). One step Backpropagation Through Time for learning input mapping in reservoir computing applied to speech recognition. Ghent University Academic Bibliography (Ghent University). 308. 521–524. 11 indexed citations

18.

Hermans, Michiel & Benjamin Schrauwen. (2010). Memory in reservoirs for high dimensional input. Ghent University Academic Bibliography (Ghent University). 10 indexed citations

19.

Hermans, Michiel & Benjamin Schrauwen. (2009). Memory in linear recurrent neural networks in continuous time. Neural Networks. 23(3). 341–355. 36 indexed citations

20.

Hermans, Michiel, Benjamin Schrauwen, Michiel D’Haene, & Dirk Stroobandt. (2008). Biologically inspired features in spiking neural networks. Ghent University Academic Bibliography (Ghent University). 328–334. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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