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Charlotte Frenkel
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- affiliation: Delft University of Technology, The Netherlands
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2020 – today
- 2024
- [j8]Theocharis Theocharides, Charlotte Frenkel, Lukas Cavigelli:
Introduction to the Special Issue on tinyML. ACM Trans. Embed. Comput. Syst. 23(3): 40:1-40:5 (2024) - [c19]Lorenzo Pes, Rick Luiken, Federico Corradi, Charlotte Frenkel:
Active Dendrites Enable Efficient Continual Learning in Time-To-First-Spike Neural Networks. AICAS 2024: 41-45 - [i18]Lorenzo Pes, Rick Luiken, Federico Corradi, Charlotte Frenkel:
Active Dendrites Enable Efficient Continual Learning in Time-To-First-Spike Neural Networks. CoRR abs/2404.19419 (2024) - [i17]Yufeng Yang, Adrian Kneip, Charlotte Frenkel:
EvGNN: An Event-driven Graph Neural Network Accelerator for Edge Vision. CoRR abs/2404.19489 (2024) - [i16]Alejandro Linares-Barranco, Luciano Prono, Robert Legenstein, Giacomo Indiveri, Charlotte Frenkel:
Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator. CoRR abs/2405.12849 (2024) - 2023
- [j7]Adnan Mehonic, Charlotte Frenkel, Eleni Vasilaki:
Editorial: Focus issue on energy-efficient neuromorphic devices, systems and algorithms. Neuromorph. Comput. Eng. 3(4): 40201 (2023) - [j6]Charlotte Frenkel, David Bol, Giacomo Indiveri:
Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence. Proc. IEEE 111(6): 623-652 (2023) - [c18]Thomas Ortner, Lorenzo Pes, Joris Gentinetta, Charlotte Frenkel, Angeliki Pantazi:
Online Spatio-Temporal Learning with Target Projection. AICAS 2023: 1-5 - [c17]Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri:
SPAIC: A sub-μW/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders. BioCAS 2023: 1-5 - [c16]Chiara Boretti, Luciano Prono, Charlotte Frenkel, Giacomo Indiveri, Fabio Pareschi, Mauro Mangia, Riccardo Rovatti, Gianluca Setti:
Event-based Classification with Recurrent Spiking Neural Networks on Low-end Micro-Controller Units. ISCAS 2023: 1-5 - [c15]Ali Safa, Jonah Van Assche, Charlotte Frenkel, André Bourdoux, Francky Catthoor, Georges G. E. Gielen:
Exploring Information-Theoretic Criteria to Accelerate the Tuning of Neuromorphic Level-Crossing ADCs. NICE 2023: 63-70 - [e1]Dhireesha Kudithipudi, Charlotte Frenkel, Suma Cardwell, James B. Aimone:
Neuro-Inspired Computational Elements Conference, NICE2023, San Antonio, TX, USA, April 11-14, 2023. ACM 2023, ISBN 978-1-4503-9947-0 [contents] - [i15]Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - [i14]Thomas Ortner, Lorenzo Pes, Joris Gentinetta, Charlotte Frenkel, Angeliki Pantazi:
Online Spatio-Temporal Learning with Target Projection. CoRR abs/2304.05124 (2023) - [i13]Shyam Narayanan, Matteo Cartiglia, Arianna Rubino, Charles Lego, Charlotte Frenkel, Giacomo Indiveri:
SPAIC: A sub-μW/Channel, 16-Channel General-Purpose Event-Based Analog Front-End with Dual-Mode Encoders. CoRR abs/2309.03221 (2023) - 2022
- [c14]Thomas Bohnstingl, Anja Surina, Maxime Fabre, Yigit Demirag, Charlotte Frenkel, Melika Payvand, Giacomo Indiveri, Angeliki Pantazi:
Biologically-inspired training of spiking recurrent neural networks with neuromorphic hardware. AICAS 2022: 218-221 - [c13]Arindam Basu, Lei Deng, Charlotte Frenkel, Xueyong Zhang:
Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions. CICC 2022: 1-8 - [c12]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand:
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. ISCAS 2022: 476-480 - [c11]Shyam Narayanan, Erika Covi, Viktor Havel, Charlotte Frenkel, Suzanne Lancaster, Quang T. Duong, Stefan Slesazeck, Thomas Mikolajick, Melika Payvand, Giacomo Indiveri:
A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices. ISCAS 2022: 717-721 - [c10]Charlotte Frenkel, Giacomo Indiveri:
ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales. ISSCC 2022: 1-3 - [i12]Matteo Cartiglia, Arianna Rubino, Shyam Narayanan, Charlotte Frenkel, Germain Haessig, Giacomo Indiveri, Melika Payvand:
Stochastic dendrites enable online learning in mixed-signal neuromorphic processing systems. CoRR abs/2201.10409 (2022) - [i11]Shyam Narayanan, Erika Covi, Viktor Havel, Charlotte Frenkel, Suzanne Lancaster, Quang T. Duong, Stefan Slesazeck, Thomas Mikolajick, Melika Payvand, Giacomo Indiveri:
A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices. CoRR abs/2202.04049 (2022) - [i10]Arindam Basu, Charlotte Frenkel, Lei Deng, Xueyong Zhang:
Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions. CoRR abs/2203.07006 (2022) - [i9]Charlotte Frenkel, Giacomo Indiveri:
ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales. CoRR abs/2208.09759 (2022) - [i8]Mayank Senapati, Manil Dev Gomony, Sherif Eissa, Charlotte Frenkel, Henk Corporaal:
THOR - A Neuromorphic Processor with 7.29G TSOP$^2$/mm$^2$Js Energy-Throughput Efficiency. CoRR abs/2212.01696 (2022) - 2021
- [j5]David Bol, Maxime Schramme, Ludovic Moreau, Pengcheng Xu, Rémi Dekimpe, Roghayeh Saeidi, Thomas Haine, Charlotte Frenkel, Denis Flandre:
SleepRunner: A 28-nm FDSOI ULP Cortex-M0 MCU With ULL SRAM and UFBR PVT Compensation for 2.6-3.6-μW/DMIPS 40-80-MHz Active Mode and 131-nW/kB Fully Retentive Deep-Sleep Mode. IEEE J. Solid State Circuits 56(7): 2256-2269 (2021) - [j4]Charlotte Frenkel:
Sparsity provides a competitive advantage. Nat. Mach. Intell. 3(9): 742-743 (2021) - [c9]Yigit Demirag, Filippo Moro, Thomas Dalgaty, Gabriele Navarro, Charlotte Frenkel, Giacomo Indiveri, Elisa Vianello, Melika Payvand:
PCM-Trace: Scalable Synaptic Eligibility Traces with Resistivity Drift of Phase-Change Materials. ISCAS 2021: 1-5 - [i7]Yigit Demirag, Filippo Moro, Thomas Dalgaty, Gabriele Navarro, Charlotte Frenkel, Giacomo Indiveri, Elisa Vianello, Melika Payvand:
PCM-trace: Scalable Synaptic Eligibility Traces with Resistivity Drift of Phase-Change Materials. CoRR abs/2102.07260 (2021) - [i6]Charlotte Frenkel, David Bol, Giacomo Indiveri:
Bottom-Up and Top-Down Neural Processing Systems Design: Neuromorphic Intelligence as the Convergence of Natural and Artificial Intelligence. CoRR abs/2106.01288 (2021) - [i5]Yigit Demirag, Charlotte Frenkel, Melika Payvand, Giacomo Indiveri:
Online Training of Spiking Recurrent Neural Networks with Phase-Change Memory Synapses. CoRR abs/2108.01804 (2021) - 2020
- [c8]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas. ISCAS 2020: 1-5 - [i4]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas. CoRR abs/2005.06318 (2020)
2010 – 2019
- 2019
- [j3]Charlotte Frenkel, Martin Lefebvre, Jean-Didier Legat, David Bol:
A 0.086-mm2 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS. IEEE Trans. Biomed. Circuits Syst. 13(1): 145-158 (2019) - [j2]Charlotte Frenkel, Jean-Didier Legat, David Bol:
MorphIC: A 65-nm 738k-Synapse/mm2 Quad-Core Binary-Weight Digital Neuromorphic Processor With Stochastic Spike-Driven Online Learning. IEEE Trans. Biomed. Circuits Syst. 13(5): 999-1010 (2019) - [c7]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A 65-nm 738k-Synapse/mm2 Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning. ISCAS 2019: 1-5 - [c6]David Bol, Maxime Schramme, Ludovic Moreau, Thomas Haine, Pengcheng Xu, Charlotte Frenkel, Remi Dekimpe, François Stas, Denis Flandre:
A 40-to-80MHz Sub-4μW/MHz ULV Cortex-M0 MCU SoC in 28nm FDSOI With Dual-Loop Adaptive Back-Bias Generator for 20μs Wake-Up From Deep Fully Retentive Sleep Mode. ISSCC 2019: 322-324 - [i3]Charlotte Frenkel, Jean-Didier Legat, David Bol:
MorphIC: A 65-nm 738k-Synapse/mm2 Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning. CoRR abs/1904.08513 (2019) - [i2]Charlotte Frenkel, Martin Lefebvre, David Bol:
Learning without feedback: Direct random target projection as a feedback-alignment algorithm with layerwise feedforward training. CoRR abs/1909.01311 (2019) - 2018
- [i1]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A 0.086-mm2 9.8-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28nm CMOS. CoRR abs/1804.07858 (2018) - 2017
- [j1]Guerric de Streel, François Stas, Thibaut Gurne, François Durant, Charlotte Frenkel, Andreia Cathelin, David Bol:
SleepTalker: A ULV 802.15.4a IR-UWB Transmitter SoC in 28-nm FDSOI Achieving 14 pJ/b at 27 Mb/s With Channel Selection Based on Adaptive FBB and Digitally Programmable Pulse Shaping. IEEE J. Solid State Circuits 52(4): 1163-1177 (2017) - [c5]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A compact phenomenological digital neuron implementing the 20 Izhikevich behaviors. BioCAS 2017: 1-4 - [c4]Charlotte Frenkel, Giacomo Indiveri, Jean-Didier Legat, David Bol:
A fully-synthesized 20-gate digital spike-based synapse with embedded online learning. ISCAS 2017: 1-4 - 2016
- [c3]Charlotte Frenkel, Jean-Didier Legat, David Bol:
Comparative analysis of redundancy schemes for soft-error detection in low-cost space applications. VLSI-SoC 2016: 1-6 - [c2]Guerric de Streel, François Stas, Thibaut Gurne, François Durant, Charlotte Frenkel, David Bol:
SleepTalker: A 28nm FDSOI ULV 802.15.4a IR-UWB transmitter SoC achieving 14pJ/bit at 27Mb/s with adaptive-FBB-based channel selection and programmable pulse shape. VLSI Circuits 2016: 1-2 - 2015
- [c1]Charlotte Frenkel, Jean-Didier Legat, David Bol:
A Partial Reconfiguration-based scheme to mitigate Multiple-Bit Upsets for FPGAs in low-cost space applications. ReCoSoC 2015: 1-7
Coauthor Index
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last updated on 2024-10-21 21:29 CEST by the dblp team
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