Nathan Laubeuf

12 papers B 1C 3Misc 1Journal 6Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO.
CoRR
Jonas Svedas, Hannah Watson, Nathan Laubeuf, Diksha Moolchandani, Abubakr Nada, Arjun Singh, Dwaipayan Biswas, James Myers, Debjyoti Bhattacharjee
2024 C conf
Adaptive Block-Scaled GeMMs on Vector Processors for DNN Training at the Edge.
VLSI-SoC
Nitish Satya Murthy, Nathan Laubeuf, Debjyoti Bhattacharjee, Francky Catthoor, Marian Verhelst
2024 — conf
Efficient DNN Training Using Vectorized Block-Scaled GeMMs with Adaptive Block Shapes.
VLSI-SoC (Selected Papers)
Nitish Satya Murthy, Nathan Laubeuf, Debjyoti Bhattacharjee, Francky Catthoor, Marian Verhelst
2023 J jnl
AIMC Modeling and Parameter Tuning for Layer-Wise Optimal Operating Point in DNN Inference.
IEEE Access
Iman Dadras, Giuseppe Maria Sarda, Nathan Laubeuf, Debjyoti Bhattacharjee, Arindam Mallik
2022 C conf
Analog Compute in Memory and Breaking Digital Number Representations.
VLSI-SoC
Nathan Laubeuf
2022 J jnl
Dynamic Quantization Range Control for Analog-in-Memory Neural Networks Acceleration.
ACM Trans. Design Autom. Electr. Syst.
Nathan Laubeuf, Jonas Doevenspeck, Ioannis A. Papistas, Michele Caselli, Stefan Cosemans, Peter Vrancx, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Francky Catthoor, Rudy Lauwereins
2022 Misc conf
Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge.
SEC
Nitish Satya Murthy, Peter Vrancx, Nathan Laubeuf, Peter Debacker, Francky Catthoor, Marian Verhelst
2021 C conf
Design-Technology Space Exploration for Energy Efficient AiMC-Based Inference Acceleration.
ISCAS
Debjyoti Bhattacharjee, Nathan Laubeuf, Stefan Cosemans, Ioannis A. Papistas, Arindam Mallik, Peter Debacker, Myung Hee Na, Diederik Verkest
2021 B conf
Noise tolerant ternary weight deep neural networks for analog in-memory inference.
IJCNN
Jonas Doevenspeck, Peter Vrancx, Nathan Laubeuf, Arindam Mallik, Peter Debacker, Diederik Verkest, Rudy Lauwereins, Wim Dehaene
2019 J jnl
FQ-Conv: Fully Quantized Convolution for Efficient and Accurate Inference.
CoRR
Bram-Ernst Verhoef, Nathan Laubeuf, Stefan Cosemans, Peter Debacker, Ioannis A. Papistas, Arindam Mallik, Diederik Verkest
2019 J jnl
Gallium-Based Thin Films for Wearable Human Motion Sensors.
Adv. Intell. Syst.
Laurent Dejace, Nathan Laubeuf, Ivan Furfaro, Stéphanie P. Lacour
2019 J jnl
Gallium-Based Thin Films for Wearable Human Motion Sensors.
Adv. Intell. Syst.
Laurent Dejace, Nathan Laubeuf, Ivan Furfaro, Stéphanie P. Lacour