Search Results - "Yon, Victor"

In‐Memory Vector‐Matrix Multiplication in Monolithic Complementary Metal–Oxide–Semiconductor‐Memristor Integrated Circuits: Design Choices, Challenges, and Perspectives by Amirsoleimani, Amirali, Alibart, Fabien, Yon, Victor, Xu, Jianxiong, Pazhouhandeh, M. Reza, Ecoffey, Serge, Beilliard, Yann, Genov, Roman, Drouin, Dominique

“…The low communication bandwidth between memory and processing units in conventional von Neumann machines does not support the requirements of emerging…”
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Exploiting Non-idealities of Resistive Switching Memories for Efficient Machine Learning by Yon, Victor, Amirsoleimani, Amirali, Alibart, Fabien, Melko, Roger G., Drouin, Dominique, Beilliard, Yann

“…Novel computing architectures based on resistive switching memories (also known as memristors or RRAMs) have been shown to be promising approaches for tackling…”
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Robust quantum dots charge autotuning using neural network uncertainty by Yon, Victor, Galaup, Bastien, Rohrbacher, Claude, Rivard, Joffrey, Godfrin, Clément, Li, Ruoyu, Kubicek, Stefan, De Greve, Kristiaan, Gaudreau, Louis, Dupont-Ferrier, Eva, Beilliard, Yann, Melko, Roger G, Drouin, Dominique

“…Abstract This study presents a machine learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention,…”
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Extraction of stress and dislocation density using in-situ curvature measurements for AlGaN and GaN on silicon growth by Charles, Matthew, Mrad, Mrad, Kanyandekwe, Joël, Yon, Victor

“…•Extraction of stress profiles in AlGaN and GaN layers from in-situ bow measurement.•Good matching between extracted profiles and XRD measurements.•Maximum…”
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X‐Ray Diffraction Microstrain Analysis for Extraction of Threading Dislocation Density of GaN Films Grown on Silicon, Sapphire, and SiC Substrates by Yon, Victor, Rochat, Névine, Charles, Matthew, Nolot, Emmanuel, Gergaud, Patrice

“…X‐Ray diffraction microstrain characterization is a technique which enables the quantification of threading dislocations by measuring the radial microstrain…”
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Unravelling the unwanted Ga incorporation effect on InGaN epilayers grown in CCS MOVPE reactors by Mrad, Mrad, Licitra, Christophe, Dussaigne, Amélie, Yon, Victor, Richy, Jérôme, Lafossas, Matthieu, Kanyandekwe, Joel, Feuillet, Guy, Charles, Matthew

“…•Ga pollution in CCS reactor strongly affects the growth process stability of InGaN.•Ga pollution decreases In incorporation and increases InGaN layer…”
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Miniaturizing neural networks for charge state autotuning in quantum dots by Czischek, Stefanie, Yon, Victor, Genest, Marc-Antoine, Roux, Marc-Antoine, Rochette, Sophie, Camirand Lemyre, Julien, Moras, Mathieu, Pioro-Ladrière, Michel, Drouin, Dominique, Beilliard, Yann, Melko, Roger G

“…Abstract A key challenge in scaling quantum computers is the calibration and control of multiple qubits. In solid-state quantum dots (QDs), the gate voltages…”
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In‐Memory Vector‐Matrix Multiplication in Monolithic Complementary Metal–Oxide–Semiconductor‐Memristor Integrated Circuits: Design Choices, Challenges, and Perspectives: Review by Amirsoleimani, Amirali, Alibart, F., Yon, Victor, Xu, Jianxiong, Pazhouhandeh, M. Reza, Ecoffey, Serge, Beilliard, Yann, Genov, Roman, Drouin, Dominique A

“…Mining big data to make predictions or decisions is the main goal of modern artificial intelligence (AI) and machine learning (ML) applications. Vast…”
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A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction by Yon, Victor, Marcotte, Frédéric, Mouny, Pierre-Antoine, Dagnew, Gebremedhin A, Kulchytskyy, Bohdan, Rochette, Sophie, Beilliard, Yann, Drouin, Dominique, Ronagh, Pooya

“…Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate…”
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Robust quantum dots charge autotuning using neural network uncertainty by Yon, Victor, Galaup, Bastien, Rohrbacher, Claude, Rivard, Joffrey, Godfrin, Clément, Li, Ruoyu, Kubicek, Stefan, De Greve, Kristiaan, Gaudreau, Louis, Dupont-Ferrier, Eva, Beilliard, Yann, Melko, Roger G, Drouin, Dominique

“…This study presents a machine-learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention, addressing…”
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Experimental Online Quantum Dots Charge Autotuning Using Neural Network by Yon, Victor, Galaup, Bastien, Rohrbacher, Claude, Rivard, Joffrey, Morel, Alexis, Leclerc, Dominic, Godfrin, Clement, Li, Ruoyu, Kubicek, Stefan, De Greve, Kristiaan, Dupont-Ferrier, Eva, Beilliard, Yann, Melko, Roger G, Drouin, Dominique

“…Spin-based semiconductor qubits hold promise for scalable quantum computing, yet they require reliable autonomous calibration procedures. This study presents…”
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Hardware-aware Training Techniques for Improving Robustness of Ex-Situ Neural Network Transfer onto Passive TiO2 ReRAM Crossbars by Drolet, Philippe, Dawant, Raphaël, Yon, Victor, Mouny, Pierre-Antoine, Valdenaire, Matthieu, Zapata, Javier Arias, Gliech, Pierre, Wood, Sean U. N, Ecoffey, Serge, Alibart, Fabien, Beilliard, Yann, Drouin, Dominique

“…Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior…”
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Miniaturizing neural networks for charge state autotuning in quantum dots by Czischek, Stefanie, Yon, Victor, Genest, Marc-Antoine, Roux, Marc-Antoine, Rochette, Sophie, Lemyre, Julien Camirand, Moras, Mathieu, Pioro-Ladrière, Michel, Drouin, Dominique, Beilliard, Yann, Melko, Roger G

“…Mach. Learn.: Sci. Technol. 3 015001 (2022) A key challenge in scaling quantum computers is the calibration and control of multiple qubits. In solid-state…”
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