Search Results - "Hirtzlin, Tifenn"

Synaptic metaplasticity in binarized neural networks by Laborieux, Axel, Ernoult, Maxence, Hirtzlin, Tifenn, Querlioz, Damien

“…While deep neural networks have surpassed human performance in multiple situations, they are prone to catastrophic forgetting: upon training a new task, they…”
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Neural-like computing with populations of superparamagnetic basis functions by Mizrahi, Alice, Hirtzlin, Tifenn, Fukushima, Akio, Kubota, Hitoshi, Yuasa, Shinji, Grollier, Julie, Querlioz, Damien

“…In neuroscience, population coding theory demonstrates that neural assemblies can achieve fault-tolerant information processing. Mapped to nanoelectronics,…”
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Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks by Bonnet, Djohan, Hirtzlin, Tifenn, Majumdar, Atreya, Dalgaty, Thomas, Esmanhotto, Eduardo, Meli, Valentina, Castellani, Niccolo, Martin, Simon, Nodin, Jean-François, Bourgeois, Guillaume, Portal, Jean-Michel, Querlioz, Damien, Vianello, Elisa

“…Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks,…”
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Digital Biologically Plausible Implementation of Binarized Neural Networks With Differential Hafnium Oxide Resistive Memory Arrays by Hirtzlin, Tifenn, Bocquet, Marc, Penkovsky, Bogdan, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

“…The brain performs intelligent tasks with extremely low energy consumption. This work takes its inspiration from two strategies used by the brain to achieve…”
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Powering AI at the edge: A robust, memristor-based binarized neural network with near-memory computing and miniaturized solar cell by Jebali, Fadi, Majumdar, Atreya, Turck, Clément, Harabi, Kamel-Eddine, Faye, Mathieu-Coumba, Muhr, Eloi, Walder, Jean-Pierre, Bilousov, Oleksandr, Michaud, Amadéo, Vianello, Elisa, Hirtzlin, Tifenn, Andrieu, François, Bocquet, Marc, Collin, Stéphane, Querlioz, Damien, Portal, Jean-Michel

“…Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered…”
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Implementation of Ternary Weights With Resistive RAM Using a Single Sense Operation Per Synapse by Laborieux, Axel, Bocquet, Marc, Hirtzlin, Tifenn, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

“…The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a significant lead for…”
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Stochastic Computing for Hardware Implementation of Binarized Neural Networks by Hirtzlin, Tifenn, Penkovsky, Bogdan, Bocquet, Marc, Klein, Jacques-Olivier, Portal, Jean-Michel, Querlioz, Damien

“…Binarized neural networks, a recently discovered class of neural networks with minimal memory requirements and no reliance on multiplication, are a fantastic…”
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Experimental Demonstration of Multilevel Resistive Random Access Memory Programming for up to Two Months Stable Neural Networks Inference Accuracy by Esmanhotto, Eduardo, Hirtzlin, Tifenn, Bonnet, Djohan, Castellani, Niccolo, Portal, Jean-Michel, Querlioz, Damien, Vianello, Elisa

“…Crossbars of resistive memories, or memristors, provide a road to reduce the energy consumption of artificial neural networks, by naturally implementing…”
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Vowel recognition with four coupled spin-torque nano-oscillators by Romera, Miguel, Talatchian, Philippe, Tsunegi, Sumito, Abreu Araujo, Flavio, Cros, Vincent, Bortolotti, Paolo, Trastoy, Juan, Yakushiji, Kay, Fukushima, Akio, Kubota, Hitoshi, Yuasa, Shinji, Ernoult, Maxence, Vodenicarevic, Damir, Hirtzlin, Tifenn, Locatelli, Nicolas, Querlioz, Damien, Grollier, Julie

“…In recent years, artificial neural networks have become the flagship algorithm of artificial intelligence 1 . In these systems, neuron activation functions are…”
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Model of the Weak Reset Process in HfO x Resistive Memory for Deep Learning Frameworks by Majumdar, Atreya, Bocquet, Marc, Hirtzlin, Tifenn, Laborieux, Axel, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

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Low voltage 25Gbps silicon Mach-Zehnder modulator in the O-band by Perez-Galacho, Diego, Baudot, Charles, Hirtzlin, Tifenn, Messaoudène, Sonia, Vulliet, Nathalie, Crozat, Paul, Boeuf, Frederic, Vivien, Laurent, Marris-Morini, Delphine

“…In this work, a 25 Gb ps silicon push-pull Mach-Zehnder modulator operating in the O-Band (1260 nm - 1360 nm) of optical communications and fabricated on a 300…”
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Model of the Weak Reset Process in HfOx Resistive Memory for Deep Learning Frameworks by Majumdar, Atreya, Bocquet, Marc, Hirtzlin, Tifenn, Laborieux, Axel, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

“…The implementation of current deep learning training algorithms is power-hungry, due to data transfer between memory and logic units. Oxide-based resistive…”
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Exploration of Low-Energy Floating-Point Flash Attention Mechanism for 18nm FD-SOI CMOS Integration at the Edge by Cornejo, Joaquin, Pouget, Filipe, Clerc, Sylvain, Hirtzlin, Tifenn, Larras, Benoit, Cathelin, Andreia, Frappe, Antoine

“…In this work we study the sizing and feasibility of a processing element for the calculation of the attention mechanism used in the Transformer models, using…”
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A memristor-based Bayesian machine by Harabi, Kamel-Eddine, Hirtzlin, Tifenn, Turck, Clément, Vianello, Elisa, Laurent, Raphaël, Droulez, Jacques, Bessière, Pierre, Portal, Jean-Michel, Bocquet, Marc, Querlioz, Damien

“…Memristors, and other emerging memory technologies, can be used to create energy-efficient implementations of neural networks. However, for certain edge…”
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Experimental Demonstration of Multilevel Resistive Random Access Memory Programming for up to Two Months Stable Neural Networks Inference Accuracy by Esmanhotto, Eduardo, Hirtzlin, Tifenn, Bonnet, Djohan, Castellani, Niccolo, Portal, Jean-Michel, Querlioz, Damien, Vianello, Elisa

“…Resistive Random Access Memory In article number 2200145, Elisa Vianello and co‐workers present a multilevel resistance states of hafnium oxide‐based resistive…”
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1S1R Optimization for High‐Frequency Inference on Binarized Spiking Neural Networks by Minguet Lopez, Joel, Rafhay, Quentin, Dampfhoffer, Manon, Reganaz, Lucas, Castellani, Niccolo, Meli, Valentina, Martin, Simon, Grenouillet, Laurent, Navarro, Gabriele, Magis, Thomas, Carabasse, Catherine, Hirtzlin, Tifenn, Vianello, Elisa, Deleruyelle, Damien, Portal, Jean‐Michel, Molas, Gabriel, Andrieu, François

“…Single memristor crossbar arrays are a very promising approach to reduce the power consumption of deep learning accelerators. In parallel, the emerging…”
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Circuit-Level Evaluation of the Generation of Truly Random Bits with Superparamagnetic Tunnel Junctions by Vodenicarevic, Damir, Locatelli, Nicolas, Mizrahi, Alice, Hirtzlin, Tifenn, Friedman, Joseph S., Grollier, Julie, Querlioz, Damien

“…Many emerging alternative models of computation require massive numbers of random bits, but their generation at low energy is currently a challenge. The…”
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In-Memory Resistive RAM Implementation of Binarized Neural Networks for Medical Applications by Penkovsky, Bogdan, Bocquet, Marc, Hirtzlin, Tifenn, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

“…The advent of deep learning has considerably accelerated machine learning development. The deployment of deep neural networks at the edge is however limited by…”
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Embracing the Unreliability of Memory Devices for Neuromorphic Computing by Bocquet, Marc, Hirtzlin, Tifenn, Klein, Jacques-Olivier, Nowak, Etienne, Vianello, Elisa, Portal, Jean-Michel, Querlioz, Damien

“…The emergence of resistive non-volatile memories opens the way to highly energy-efficient computation near- or in-memory. However, this type of computation is…”
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Bayesian Metaplasticity from Synaptic Uncertainty by Bonnet, Djohan, Hirtzlin, Tifenn, Januel, Tarcisius, Dalgaty, Thomas, Querlioz, Damien, Vianello, Elisa

“…Catastrophic forgetting remains a challenge for neural networks, especially in lifelong learning scenarios. In this study, we introduce MEtaplasticity from…”
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