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Reviving holographic photonic integration Autoría: Brunner, Daniel

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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Impact of white noise in artificial neural networks trained for classification: performance and noise mitigation strategies Autoría: Semenova, Nadezhda, Brunner, Daniel

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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3

The thin line for optical neural networks towards broad practical relevance Autoría: Skalli, Anas, Brunner, Daniel

Published 2026

Fuente: arXiv

Tipo de material: Preprint

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Dynamic Consumer Demand at Large Scale Autoría: Brunner, Daniel, Heiss, Florian, Schmidt, Anna B.

Published 2026

Fuente: arXiv

Tipo de material: Preprint

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5

Nonlinear integrated optical resonators for optical fibre data recovery Autoría: Boikov, Ivan K., Brunner, Daniel, De Rossi, Alfredo

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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3D Photonic integration leveraging hybrid-confinement circuits Autoría: Sharma, Kanhaya, Grabulosa, Adrià, Jung, Erik, Brunner, Daniel

Published 2026

Fuente: arXiv

Tipo de material: Preprint

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7

A spiking photonic neural network of 40.000 neurons, trained with rank-order coding for leveraging sparsity Autoría: Talukder, Ria, Skalli, Anas, Porte, Xavier, Thorpe, Simon, Brunner, Daniel

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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8

Annealing-inspired training of an optical neural network with ternary weights Autoría: Skalli, Anas, Goldmann, Mirko, Haghighi, Nasibeh, Reitzenstein, Stephan, Lott, James A., Brunner, Daniel

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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9

Experimental reservoir computing with diffractively coupled VCSELs Autoría: Pflüger, Moritz, Brunner, Daniel, Heuser, Tobias, Lott, James A., Reitzenstein, Stephan, Fischer, Ingo

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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10

Principles and Metrics of Extreme Learning Machines Using a Highly Nonlinear Fiber Autoría: Hary, Mathilde, Brunner, Daniel, Leybov, Lev, Ryczkowski, Piotr, Dudley, John M., Genty, Goëry

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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11

Expressivity Limits of Quantum Reservoir Computing Autoría: Schütte, Nils-Erik, Götting, Niclas, Müntinga, Hauke, List, Meike, Brunner, Daniel, Gies, Christopher

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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12

Model-free front-to-end training of a large high performance laser neural network Autoría: Skalli, Anas, Sunada, Satoshi, Goldmann, Mirko, Gebski, Marcin, Reitzenstein, Stephan, Lott, James A., Czyszanowski, Tomasz, Brunner, Daniel

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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13

Limits of nonlinear and dispersive fiber propagation for an optical fiber-based extreme learning machine Autoría: Ermolaev, Andrei V., Hary, Mathilde, Leybov, Lev, Ryczkowski, Piotr, Skalli, Anas, Brunner, Daniel, Genty, Goëry, Dudley, John M.

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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14

LEXam: Benchmarking Legal Reasoning on 340 Law Exams Autoría: Fan, Yu, Ni, Jingwei, Merane, Jakob, Tian, Yang, Hermstrüwer, Yoan, Huang, Yinya, Akhtar, Mubashara, Salimbeni, Etienne, Geering, Florian, Dreyer, Oliver, Brunner, Daniel, Leippold, Markus, Sachan, Mrinmaya, Stremitzer, Alexander, Engel, Christoph, Ash, Elliott, Niklaus, Joel

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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15

SwiLTra-Bench: The Swiss Legal Translation Benchmark Autoría: Niklaus, Joel, Merane, Jakob, Nenadic, Luka, Ahmadi, Sina, Gao, Yingqiang, Chevalley, Cyrill A. H., Humbel, Claude, Gösken, Christophe, Tanzi, Lorenzo, Lüthi, Thomas, Palombo, Stefan, Poff, Spencer, Yang, Boling, Wu, Nan, Guillod, Matthew, Mamié, Robin, Brunner, Daniel, Pereyra, Julio, Grupen, Niko

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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16

Training of Physical Neural Networks Autoría: Momeni, Ali, Rahmani, Babak, Scellier, Benjamin, Wright, Logan G., McMahon, Peter L., Wanjura, Clara C., Li, Yuhang, Skalli, Anas, Berloff, Natalia G., Onodera, Tatsuhiro, Oguz, Ilker, Morichetti, Francesco, del Hougne, Philipp, Gallo, Manuel Le, Sebastian, Abu, Mirhoseini, Azalia, Zhang, Cheng, Marković, Danijela, Brunner, Daniel, Moser, Christophe, Gigan, Sylvain, Marquardt, Florian, Ozcan, Aydogan, Grollier, Julie, Liu, Andrea J., Psaltis, Demetri, Alù, Andrea, Fleury, Romain

Published 2024

Fuente: arXiv

Tipo de material: Preprint

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17

Roadmap on Neuromorphic Photonics Autoría: Brunner, Daniel, Shastri, Bhavin J., Qadasi, Mohammed A. Al, Ballani, H., Barbay, Sylvain, Biasi, Stefano, Bienstman, Peter, Bilodeau, Simon, Bogaerts, Wim, Böhm, Fabian, Brennan, G., Buckley, Sonia, Cai, Xinlun, Strinati, Marcello Calvanese, Canakci, B., Charbonnier, Benoit, Chemnitz, Mario, Chen, Yitong, Cheung, Stanley, Chiles, Jeff, Choi, Suyeon, Christodoulides, Demetrios N., Chrostowski, Lukas, Chu, J., Clegg, J. H., Cletheroe, D., Conti, Claudio, Dai, Qionghai, Di Lauro, Luigi, Diamantopoulos, Nikolaos Panteleimon, Dinc, Niyazi Ulas, Ewaniuk, Jacob, Fan, Shanhui, Fang, Lu, Franchi, Riccardo, Freire, Pedro, Gentilini, Silvia, Gigan, Sylvain, Giorgi, Gian Luca, Gkantsidis, C., Gladrow, J., Goi, Elena, Goldmann, M., Grabulosa, A., Gu, Min, Guo, Xianxin, Hejda, Matěj, Horst, F., Hsieh, Jih Liang, Hu, Jianqi, Hu, Juejun, Huang, Chaoran, Hurtado, Antonio, Jaurigue, Lina, Kalinin, K. P., Kopae, Morteza Kamalian, Kelly, D. J., Khajavikhan, Mercedeh, Kremer, H., Laydevant, Jeremie, Lederman, Joshua C., Lee, Jongheon, Lenstra, Daan, Li, Gordon H. Y., Li, Mo, Li, Yuhang, Lin, Xing, Lin, Zhongjin, Lis, Mieszko, Lüdge, Kathy, Lugnan, Alessio, Lupo, Alessandro, Lvovsky, A. I., Manuylovich, Egor, Marandi, Alireza, Marchesin, Federico, Massar, Serge, McCaughan, Adam N., McMahon, Peter L., Pegios, Miltiadis Moralis, Morandotti, Roberto, Moser, Christophe, Moss, David J., Mukherjee, Avilash, Nikdast, Mahdi, Offrein, B. J., Oguz, Ilker, Oripov, Bakhrom, O'Shea, G., Ozcan, Aydogan, Parmigiani, F., Pasricha, Sudeep, Pavanello, Fabio, Pavesi, Lorenzo, Peserico, Nicola, Pickup, L., Pierangeli, Davide, Pleros, Nikos, Porte, Xavier, Primavera, Bryce A., Prucnal, Paul, Psaltis, Demetri, Puts, Lukas, Qiao, Fei, Rahmani, B., Raineri, Fabrice, Ocampo, Carlos A. Ríos, Robertson, Joshua, Romeira, Bruno, Carmes, Charles Roques, Rotenberg, Nir, Rowstron, A., Schoenhardt, Steffen, Schwartz, Russell L . T., Shainline, Jeffrey M., Shekhar, Sudip, Skalli, Anas, Sohoni, Mandar M., Sorger, Volker J., Soriano, Miguel C., Spall, James, Stabile, Ripalta, Stiller, Birgit, Sunada, Satoshi, Tefas, Anastasios, Tossoun, Bassem, Tsakyridis, Apostolos, Turitsyn, Sergei K., Van der Sande, Guy, Van Vaerenbergh, Thomas, Veraldi, Daniele, Verschaffelt, Guy, Vlieg, E. A., Wang, Hao, Wang, Tianyu, Wetzstein, Gordon, Wright, Logan G., Wu, Changming, Wu, Chu, Wu, Jiamin, Xia, Fei, Xu, Xingyuan, Yang, Hangbo, Yao, Weiming, Yildirim, Mustafa, Yoo, S. J. Ben, Youngblood, Nathan, Zambrini, Roberta, Zhang, Haiou, Zhang, Weipeng

Published 2025

Fuente: arXiv

Tipo de material: Preprint

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Reviving holographic photonic integration Autoría: Brunner, Daniel

Impact of white noise in artificial neural networks trained for classification: performance and noise mitigation strategies Autoría: Semenova, Nadezhda, Brunner, Daniel

The thin line for optical neural networks towards broad practical relevance Autoría: Skalli, Anas, Brunner, Daniel

Dynamic Consumer Demand at Large Scale Autoría: Brunner, Daniel, Heiss, Florian, Schmidt, Anna B.

Nonlinear integrated optical resonators for optical fibre data recovery Autoría: Boikov, Ivan K., Brunner, Daniel, De Rossi, Alfredo

3D Photonic integration leveraging hybrid-confinement circuits Autoría: Sharma, Kanhaya, Grabulosa, Adrià, Jung, Erik, Brunner, Daniel

A spiking photonic neural network of 40.000 neurons, trained with rank-order coding for leveraging sparsity Autoría: Talukder, Ria, Skalli, Anas, Porte, Xavier, Thorpe, Simon, Brunner, Daniel

Annealing-inspired training of an optical neural network with ternary weights Autoría: Skalli, Anas, Goldmann, Mirko, Haghighi, Nasibeh, Reitzenstein, Stephan, Lott, James A., Brunner, Daniel

Experimental reservoir computing with diffractively coupled VCSELs Autoría: Pflüger, Moritz, Brunner, Daniel, Heuser, Tobias, Lott, James A., Reitzenstein, Stephan, Fischer, Ingo

Principles and Metrics of Extreme Learning Machines Using a Highly Nonlinear Fiber Autoría: Hary, Mathilde, Brunner, Daniel, Leybov, Lev, Ryczkowski, Piotr, Dudley, John M., Genty, Goëry

Expressivity Limits of Quantum Reservoir Computing Autoría: Schütte, Nils-Erik, Götting, Niclas, Müntinga, Hauke, List, Meike, Brunner, Daniel, Gies, Christopher

Model-free front-to-end training of a large high performance laser neural network Autoría: Skalli, Anas, Sunada, Satoshi, Goldmann, Mirko, Gebski, Marcin, Reitzenstein, Stephan, Lott, James A., Czyszanowski, Tomasz, Brunner, Daniel

Limits of nonlinear and dispersive fiber propagation for an optical fiber-based extreme learning machine Autoría: Ermolaev, Andrei V., Hary, Mathilde, Leybov, Lev, Ryczkowski, Piotr, Skalli, Anas, Brunner, Daniel, Genty, Goëry, Dudley, John M.

Search Results - Brunner, Daniel

Reviving holographic photonic integration Autoría: Brunner, Daniel

Impact of white noise in artificial neural networks trained for classification: performance and noise mitigation strategies Autoría: Semenova, Nadezhda, Brunner, Daniel

The thin line for optical neural networks towards broad practical relevance Autoría: Skalli, Anas, Brunner, Daniel

Dynamic Consumer Demand at Large Scale Autoría: Brunner, Daniel, Heiss, Florian, Schmidt, Anna B.

Nonlinear integrated optical resonators for optical fibre data recovery Autoría: Boikov, Ivan K., Brunner, Daniel, De Rossi, Alfredo

3D Photonic integration leveraging hybrid-confinement circuits Autoría: Sharma, Kanhaya, Grabulosa, Adrià, Jung, Erik, Brunner, Daniel

A spiking photonic neural network of 40.000 neurons, trained with rank-order coding for leveraging sparsity Autoría: Talukder, Ria, Skalli, Anas, Porte, Xavier, Thorpe, Simon, Brunner, Daniel

Annealing-inspired training of an optical neural network with ternary weights Autoría: Skalli, Anas, Goldmann, Mirko, Haghighi, Nasibeh, Reitzenstein, Stephan, Lott, James A., Brunner, Daniel

Experimental reservoir computing with diffractively coupled VCSELs Autoría: Pflüger, Moritz, Brunner, Daniel, Heuser, Tobias, Lott, James A., Reitzenstein, Stephan, Fischer, Ingo

Principles and Metrics of Extreme Learning Machines Using a Highly Nonlinear Fiber Autoría: Hary, Mathilde, Brunner, Daniel, Leybov, Lev, Ryczkowski, Piotr, Dudley, John M., Genty, Goëry

Expressivity Limits of Quantum Reservoir Computing Autoría: Schütte, Nils-Erik, Götting, Niclas, Müntinga, Hauke, List, Meike, Brunner, Daniel, Gies, Christopher

Model-free front-to-end training of a large high performance laser neural network Autoría: Skalli, Anas, Sunada, Satoshi, Goldmann, Mirko, Gebski, Marcin, Reitzenstein, Stephan, Lott, James A., Czyszanowski, Tomasz, Brunner, Daniel

Limits of nonlinear and dispersive fiber propagation for an optical fiber-based extreme learning machine Autoría: Ermolaev, Andrei V., Hary, Mathilde, Leybov, Lev, Ryczkowski, Piotr, Skalli, Anas, Brunner, Daniel, Genty, Goëry, Dudley, John M.

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