Browsing by author "Laubeuf, Nathan"
Now showing items 1-8 of 8
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AIMC Modeling and Parameter Tuning for Layer-Wise Optimal Operating Point in DNN Inference
Dadras, Iman; Sarda, Giuseppe; Laubeuf, Nathan; Bhattacharjee, Debjyoti; Mallik, Arindam (2023) -
Analog Compute in Memory and Breaking Digital Number Representations
Laubeuf, Nathan (2022) -
Design-Technology Space Exploration For Energy Efficient AiMC-based Inference Acceleration
Bhattacharjee, Debjyoti; Laubeuf, Nathan; Cosemans, Stefan; Papistas, Ioannis; Mallik, Arindam; Debacker, Peter; Na, Myung Hee; Verkest, Diederik (2021) -
Dynamic Quantization Range Control for Analog-in-Memory Neural Networks Acceleration
Laubeuf, Nathan; Doevenspeck, Jonas; Papistas, Ioannis; Caselli, Michele; Cosemans, Stefan; Vrancx, Peter; Bhattacharjee, Debjyoti; Mallik, Arindam; Debacker, Peter; Verkest, Diederik; Catthoor, Francky; Lauwereins, Rudy (2022-09) -
FQ-Conv: Fully quantized convolution for efficient and accurate inference
Verhoef, Bram; Laubeuf, Nathan; Cosemans, Stefan; Debacker, Peter; Papistas, Ioannis; Mallik, Arindam; Verkest, Diederik (2019) -
Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge
Satya Murthy, Nitish; Vrancx, Peter; Laubeuf, Nathan; Debacker, Peter; Catthoor, Francky; Verhelst, Marian (2022) -
Noise tolerant ternary weight deep neural networks for analog in-memory inference
Doevenspeck, Jonas; Vrancx, Peter; Laubeuf, Nathan; Mallik, Arindam; Debacker, Peter; Verkest, Diederik; Lauwereins, Rudy; Dehaene, Wim (2021) -
Novel memory devices tailored to analog in-memory computing for neural network inference
Cosemans, Stefan; Doevenspeck, Jonas; Verhoef, Bram; Papistas, Ioannis; Laubeuf, Nathan; Bhattacharjee, Debjyoti; Catthoor, Francky; Debacker, Peter; Verkest, Diederik; Rao, Siddharth; Subhechha, Subhali; Kar, Gouri Sankar; Furnemont, Arnaud (2020-09)