Thomas Van Vaerenbergh

According to our database, Thomas Van Vaerenbergh authored at least 25 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Distributed Binary Optimization with In-Memory Computing: An Application for the SAT Problem.

Xiangyi Zhang, Ignacio Rozada, Fabian Böhm, Elisabetta Valiante, Moslem Noori, Thomas Van Vaerenbergh, Chan-Woo Yang, Giacomo Pedretti, Masoud Mohseni, Raymond G. Beausoleil

CoRR, 2024

Photonic KAN: a Kolmogorov-Arnold network inspired efficient photonic neuromorphic architecture.

Yiwei Peng, Sean Hooten, Xinling Yu, Thomas Van Vaerenbergh, Yuan Yuan, Xian Xiao, Bassem Tossoun, Stanley Cheung, Marco Fiorentino, Raymond G. Beausoleil

CoRR, 2024

Separable Operator Networks.

Xinling Yu, Sean Hooten, Ziyue Liu, Yequan Zhao, Marco Fiorentino, Thomas Van Vaerenbergh, Zheng Zhang

CoRR, 2024

Computing High-Degree Polynomial Gradients in Memory.

Tinish Bhattacharya, George Higgins Hutchinson, Giacomo Pedretti, X. Sheng, Jim Ignowski, Thomas Van Vaerenbergh, Raymond G. Beausoleil, John Paul Strachan, Dmitri B. Strukov

CoRR, 2024

Optical Neural Networks with Tensor Compression and Photonic Memory.

Xian Xiao, Stanley Cheung, Bassem Tossoun, Thomas Van Vaerenbergh, Geza Kurczveil, Raymond G. Beausoleil

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2024

20 GHz Silicon Integrated Optical Ternary Content Addressable Memory (CAM) Cell.

George Giamougiannis, Christos Pappas, Theodoros Moschos, Apostolos Tsakyridis, Miltiadis Moralis-Pegios, Christos Vagionas, Yanir London, Thomas Van Vaerenbergh, Bassem Tossoun, Nikos Pleros

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2024

Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines.

Mohammad Hizzani, Arne Heittmann, George Higgins Hutchinson, Dmitrii Dobrynin, Thomas Van Vaerenbergh, Tinish Bhattacharya, Adrien Renaudineau, Dmitri B. Strukov, John Paul Strachan

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Invited: Neuromorphic Architectures Based on Augmented Silicon Photonics Platforms.

Matej Hejda, Federico Marchesin, George Papadimitriou, Dimitris Gizopoulos, Benoît Charbonnier, Régis Orobtchouk, Peter Bienstman, Thomas Van Vaerenbergh, Fabio Pavanello

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Automatic differentiation accelerated shape optimization approaches to photonic inverse design on rectilinear simulation grids.

Sean Hooten, Peng Sun, Liron Gantz, Marco Fiorentino, Raymond G. Beausoleil, Thomas Van Vaerenbergh

CoRR, 2023

NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS.

Fabio Pavanello, Cédric Marchand, Ian O'Connor, Régis Orobtchouk, Fabien Mandorlo, Xavier Letartre, Sébastien Cueff, Elena-Ioana Vatajelu, Giorgio Di Natale, Benoit Cluzel, Aurelien Coillet, Benoît Charbonnier, Pierre Noe, Frantisek Kavan, Martin Zoldak, Michal Szaj, Peter Bienstman, Thomas Van Vaerenbergh, Ulrich Rührmair, Paulo F. Flores, Luís Guerra e Silva, Ricardo Chaves, Luís Miguel Silveira, Mariano Ceccato, Dimitris Gizopoulos, George Papadimitriou, Vasileios Karakostas, Axel Brando, Francisco J. Cazorla, Ramon Canal, Pau Closas, Adria Gusi-Amigo, Paolo Crovetti, Alessio Carpegna, Tzamn Melendez Carmona, Stefano Di Carlo, Alessandro Savino

CoRR, 2023

Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies.

Fabio Pavanello, Elena-Ioana Vatajelu, Alberto Bosio, Thomas Van Vaerenbergh, Peter Bienstman, Benoît Charbonnier, Alessio Carpegna, Stefano Di Carlo, Alessandro Savino

Proceedings of the 41st IEEE VLSI Test Symposium, 2023

Wavelength-Parallel Photonic Tensor Core Based on Multi-FSR Microring Resonator Crossbar Array.

Xian Xiao, Stanley Cheung, Sean Hooten, Yiwei Peng, Bassem Tossoun, Thomas Van Vaerenbergh, Geza Kurczveil, Raymond G. Beausoleil

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2023

EUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS.

Fabio Pavanello, Cédric Marchand, Ian O'Connor, Régis Orobtchouk, Fabien Mandorlo, Xavier Letartre, Sébastien Cueff, Elena-Ioana Vatajelu, Giorgio Di Natale, Benoit Cluzel, Aurelien Coillet, Benoît Charbonnier, Pierre Noe, Frantisek Kavan, Martin Zoldak, Michal Szaj, Peter Bienstman, Thomas Van Vaerenbergh, Ulrich Rührmair, Paulo F. Flores, Luís Guerra e Silva, Ricardo Chaves, Luís Miguel Silveira, Mariano Ceccato, Dimitris Gizopoulos, George Papadimitriou, Vasileios Karakostas, Axel Brando, Francisco J. Cazorla, Ramon Canal, Pau Closas, Adria Gusi-Amigo, Paolo Crovetti, Alessio Carpegna, Tzamn Melendez Carmona, Stefano Di Carlo, Alessandro Savino

Proceedings of the IEEE European Test Symposium, 2023

2022

Inverse-Designed Dual Layer c-Si/SiN Vertical Grating Couplers Tested on 300mm Wafers.

Sean Hooten, Mudit Jain, Thomas Van Vaerenbergh, Peng Sun, Quentin Wilmart, M. Ashkan Seyedi, Zhihong Huang, Marco Fiorentino, Raymond G. Beausoleil

Proceedings of the 2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC), 2022

2021

Inverse Design of Grating Couplers Using the Policy Gradient Method from Reinforcement Learning.

Sean Hooten, Thomas Van Vaerenbergh, Raymond G. Beausoleil

CoRR, 2021

Compact and inexpensive photonic Ising machines based on optoelectronic oscillators.

Guy van der Sande, Fabian Böhm, Thomas Van Vaerenbergh, Guy Verschaffelt

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2021

2020

Suppressing amplitude inhomogeneity enhances computational performance of Ising machines: why the choice of nonlinearity matters.

Fabian Böhm, Thomas Van Vaerenbergh, Guy Verschaffelt, Guy van der Sande

CoRR, 2020

Integrated Green DWDM Photonics for Next-Gen High-Performance Computing.

Di Liang, Geza Kurczveil, Zhihong Huang, Binhao Wang, Antoine Descos, Sudharsanan Srinivasan, Yingtao Hu, Xiaoge Zeng, Wayne V. Sorin, Stanley Cheung, Songtao Liu, Peng Sun, Thomas Van Vaerenbergh, Marco Fiorentino, John E. Bowers, Raymond G. Beausoleil

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

Classical Adiabatic Annealing in Memristor Hopfield Neural Networks for Combinatorial Optimization.

Suhas Kumar, Thomas Van Vaerenbergh, John Paul Strachan

Proceedings of the International Conference on Rebooting Computing, 2020

2019

Harnessing Intrinsic Noise in Memristor Hopfield Neural Networks for Combinatorial Optimization.

Fuxi Cai, Suhas Kumar, Thomas Van Vaerenbergh, Rui Liu, Can Li, Shimeng Yu, Qiangfei Xia, J. Joshua Yang, Raymond G. Beausoleil, Wei Lu, John Paul Strachan

CoRR, 2019

Future Computing Systems (FCS) to Support "Understanding" Capability.

Raymond G. Beausoleil, Thomas Van Vaerenbergh, Kirk Bresniker, Catherine Graves, Kimberly Keeton, Suhas Kumar, Can Li, Dejan S. Milojicic, Sergey Serebryakov, John Paul Strachan

Proceedings of the 2019 IEEE International Conference on Rebooting Computing, 2019

2017

Demonstration of a Coherent Tunable Amplifier for All-Optical Ising Machines.

Thomas Van Vaerenbergh, Gabriel Joe Mendoza, Dave Kielpinski, Jason S. Pelc, Nikolas A. Tezak, Ranojoy Bose, Charles M. Santori, Raymond G. Beausoleil

Proceedings of the IEEE International Conference on Rebooting Computing, 2017

2016

Information processing with large-scale optical integrated circuits.

David Kielpinski, Ranojoy Bose, Jason S. Pelc, Thomas Van Vaerenbergh, Gabriel Joe Mendoza, Nikolas A. Tezak, Raymond G. Beausoleil

Proceedings of the IEEE International Conference on Rebooting Computing, 2016

2015

Towards Trainable Media: Using Waves for Neural Network-Style Training.

Michiel Hermans, Thomas Van Vaerenbergh

CoRR, 2015

2014

Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns.

Martin Andre Agnes Fiers, Thomas Van Vaerenbergh, Francis Wyffels, David Verstraeten, Benjamin Schrauwen, Joni Dambre, Peter Bienstman

IEEE Trans. Neural Networks Learn. Syst., 2014