Publications

2024

• Brückerhoff-Plückelmann, F, Borras, H, Klein, B, Varri, A, Becker, M, Dijkstra, J, Brückerhoff, M, Wright, CD, Salinga, M, Bhaskaran, H, Risse, B, Fröning, H, and Pernice, W. 2024. “Probabilistic photonic computing with chaotic light.” Nature Communications, № 15 (1): 10445–10445. doi: 10.1038/s41467-024-54931-6.
• Becker, Marlon, Butz, Marco, Lemli, David, Schuck, Carsten, and Risse, Benjamin. 2024. “Learning Proposal Distributions in Simulated Annealing via Template Networks: A Case Study in Nanophotonic Inverse Design.” in Pattern Recognition, Vol. 27 of 27th International Conference ICPR 2024, edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya and Umapada Pal. Heidelberg: Springer. doi: https://doi.org/10.1007/978-3-031-78186-5_13.
• Tertilt, Henri, Mensing, Jonas: Becker Marlon: van der Wiel Wilfred G., and Bobbert, Peter A.: Heuer Andreas. 2024. “Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks.” Physical Review Applied, № 22 (2) doi: 10.1103/PhysRevApplied.22.024063.
• Schulte, L, Butz, M, Becker, M, Risse, B, and Schuck, C. 2024. “Accelerating Finite-Difference Frequency-Domain Simulations for Inverse Design Problems in Nanophotonics using Deep Learning.” Journal of the Optical Society of America B, № 41 (4): 1039–1046. doi: 10.1364/JOSAB.506159.

2023

• Wendland, D, Becker, M, Brückerhoff-Plückelmann, F, Bente, I, Busch, K, Risse, B, and Pernice, WH. 2023. “Coherent dimension reduction with integrated photonic circuits exploiting tailored disorder.” Journal of the Optical Society of America B, № 40 (3): B35–B40.
• Butz, M, Leifhelm, A, Becker, M, Risse, B, and Schuck, C. 2023. “A Universal Approach to Nanophotonic Inverse Design through Reinforcement Learning.” in CLEO 2023, paper STh4G.3, edited by Optica Publishing Group. Washington, DC: Optica. doi: 10.1364/CLEO_SI.2023.STh4G.3.
• Butz, Marco, Leifhelm, Alexander, Becker, Marlon, Risse, Benjamin, and Schuck, Carsten. 2023. “A Novel Approach to Nanophotonic Black-Box Optimization Through Reinforcement Learning.” in Q 30 Nano-optics, edited by DPG. Bad Honnef: Deutsche Physikalische Gesellschaft.
• Becker, Marlon, Riegelmeyer, Jan, Seyfried, Maximilian, Ravoo, Bart-Jan, Schuck, Carsten, and Risse, Benjamin. 2023. “Adaptive Photo-Chemical Nonlinearities for Optical Neural Networks.” Advanced Intelligent Systems, № ‎ 5 (12) 2300229. doi: 10.1002/aisy.202300229 .
• Brückerhoff-Plückelmann, Frank, Bente, Ivonne, Becker, Marlon, Vollmar, Niklas, Farmakidis, Nikolaos, Lomonte, Emma, Lenzini, Francesco, Wright, CDavid, Bhaskaran, Harish, Salinga, Martin, Risse, Benjamin, and Pernice, Wolfram HP. 2023. “Event-driven adaptive optical neural network.” Science advances, № 9 (42): eadi9127. doi: 10.1126/sciadv.adi9127.
• Purk, M., Fujarski, M., Becker, M., Warnecke, T., and Varghese, J. 2023. “Utilizing a tablet-based artificial intelligence system to assess movement disorders in a prospective study.” Scientific Reports, № 13 (1) doi: 10.1038/s41598-023-37388-3.
• Becker, Marlon, Drees, Dominik, Brückerhoff-Plückelmann, Frank, Schuck, Carsten, Pernice, Wolfram, and Risse, Benjamin. 2023. “Activation Functions in Non-Negative Neural Networks.” contributed to the Machine Learning and the Physical Sciences Workshop, NeurIPS, New Orleans
• Becker, Marlon, Riegelmeyer, Jan, Seyfried, Maximilian David, Ravoo, Bart Jan, Schuck, Carsten, and Risse, Benjamin. 2023. “Adaptive Photochemical Nonlinearities for Optical Neural Networks.” Advanced Intelligent Systems, № 5 (12) doi: 10.1002/aisy.202300229.
• Becker, Marlon, Butz, Marco, Lemli, David, Schuck, Carsten, and Risse, Benjamin. 2023. “Combinatorial Optimization via Memory Metropolis: Template Networks for Proposal Distributions in Simulated Annealing applied to Nanophotonic Inverse Design.” contributed to the Neural Information Processing Systems (NeurIPS) Workshop on AI for Accelerated Materials Design (AI4Mat-2023), New Orleans

2022

• Riegelmeyer, Jan, Eich, Alexander, Becker, Marlon, Risse, Benjamin, and Schuck, Carsten. 2022. “Development of a nanophotonic nonlinear unit for optical artificial neural networks.” contributed to the DPG Springmeeting 2022, Erlangen
• Butz, Marco, Leifhelm, Alexander, Becker, Marlon, Risse, Benjamin, and Schuck, Carsten. 2022. “Inverse Design of Nanophotonic Devices based on Reinforcement Learning.” in Q 38 Photonics II, edited by DPG. Bad Honnef: Deutsche Physikalische Gesellschaft.
• Tertilt, Henri, Bakker, Jesse, Becker, Marlon, de Wilde, Bram, Klanberg, Indrek, Geurts, Bernard J., van der Wiel, Wilfred G., Heuer, Andreas, and Bobbert, Peter A. 2022. “Hopping-transport mechanism for reconfigurable logic in disordered dopant networks.” Physical Review Applied, № 17 (6): 064025. doi: 10.1103/PhysRevApplied.17.064025.

2018

• Friedman, R, Khalid, S, Santamaría, CA, Arutyunova, E, Becker, M, Boyd, KJ, Christensen, M, Coimbra, JTS, Concilio, S, Daday, C, van Eerden, FJ, Fernandes, PA, Gräter, F, Hakobyan, D, Heuer, A, Karathanou, K, Keller, F, Lemieux, MJ, Marrink, SJ, May, ER, Mazumdar, A, Naftalin, R, Pickholz, M, Piotto, S, Pohl, P, Quinn, P, Ramos, MJ, Schiøtt, B, Sengupta, D, Sessa, L, Vanni, S, Zeppelin, T, Zoni, V, Bondar, A-N, and Domene, C. 2018. “Understanding Conformational Dynamics of Complex Lipid Mixtures Relevant to Biology.” Journal of Membrane Biology, № 251 (5): 609–631.