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2020 – today
- 2024
[c15]Pascal Alexander Hager, Bert Moons, Stefan Cosemans, Ioannis A. Papistas, Bram Rooseleer, Jeroen Van Loon, Roel Uytterhoeven, Florian Zaruba, Spyridoula Koumousi, Milos Stanisavljevic, Stefan Mach, Sebastiaan Mutsaards, Riduan Khaddam Aljameh, Gua Hao Khov, Brecht Machiels, Cristian Olar, Anastasios Psarras, Sander Geursen, Jeroen Vermeeren, Yi Lu, Abhishek Maringanti, Deepak Ameta, Leonidas Katselas, Noah Hütter, Manuel Schmuck, Swetha Sivadas, Karishma Sharma, Manuel Oliveira, Ramon Aerne, Nitish Sharma, Timir Soni, Beatrice Bussolino, Djordje Pesut, Michele Pallaro, Andrei Podlesnii, Alexios Lyrakis, Yannick Ruffiner, Martino Dazzi, Johannes Thiele, Koen Goetschalckx, Nazareno Bruschi, Jonas Doevenspeck, Bram Verhoef, Stefan Linz, Giuseppe Garcea, Jonathan Ferguson, Ioannis Koltsidas, Evangelos Eleftheriou:
11.3 Metis AIPU: A 12nm 15TOPS/W 209.6TOPS SoC for Cost- and Energy-Efficient Inference at the Edge. ISSCC 2024: 212-214- 2023
- [c14]Yunqiang Li, Jan C. van Gemert, Torsten Hoefler, Bert Moons, Evangelos Eleftheriou, Bram-Ernst Verhoef:
Differentiable Transportation Pruning. ICCV 2023: 16911-16921 - [i7]Yunqiang Li, Jan C. van Gemert, Torsten Hoefler, Bert Moons, Evangelos Eleftheriou, Bram-Ernst Verhoef:
Differentiable Transportation Pruning. CoRR abs/2307.08483 (2023) - 2021
- [c13]Bert Moons, Parham Noorzad, Andrii Skliar, Giovanni Mariani, Dushyant Mehta, Chris Lott, Tijmen Blankevoort:
Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces. ICCV 2021: 12209-12218 - 2020
- [i6]Bert Moons, Parham Noorzad, Andrii Skliar, Giovanni Mariani, Dushyant Mehta, Chris Lott, Tijmen Blankevoort:
Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces. CoRR abs/2012.08859 (2020)
2010 – 2019
- 2019
- [j4]Daniel Bankman
, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An Always-On 3.8 $\mu$ J/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS. IEEE J. Solid State Circuits 54(1): 158-172 (2019) - 2018
- [j3]Koen Goetschalckx, Bert Moons, Steven Lauwereins, Martin Andraud, Marian Verhelst:
Optimized Hierarchical Cascaded Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 884-894 (2018) - [c12]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An always-on energy-accuracy-scalable binary CNN processor with all memory on chip in 28nm CMOS. CICC 2018: 1-4 - [c11]Gage Hills, Daniel Bankman, Bert Moons, Lita Yang, Jake Hillard, Alex Kahng, Rebecca Park, Marian Verhelst, Boris Murmann, Max M. Shulaker, H.-S. Philip Wong, Subhasish Mitra:
TRIG: hardware accelerator for inference-based applications and experimental demonstration using carbon nanotube FETs. DAC 2018: 74:1-74:10 - [c10]Lita Yang, Daniel Bankman, Bert Moons, Marian Verhelst, Boris Murmann:
Bit Error Tolerance of a CIFAR-10 Binarized Convolutional Neural Network Processor. ISCAS 2018: 1-5 - [c9]Daniel Bankman, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An always-on 3.8μJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS. ISSCC 2018: 222-224 - [c8]Koen Goetschalckx, Bert Moons, Patrick Wambacq, Marian Verhelst:
Efficiently Combining SVD, Pruning, Clustering and Retraining for Enhanced Neural Network Compression. EMDL@MobiSys 2018: 1-6 - [i5]Matthijs Van Keirsbilck, Bert Moons, Marian Verhelst:
Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion. CoRR abs/1803.04840 (2018) - [i4]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An Always-On Energy-Accuracy-Scalable Binary CNN Processor With All Memory On Chip in 28nm CMOS. CoRR abs/1804.05554 (2018) - 2017
- [j2]Bert Moons, Marian Verhelst:
An Energy-Efficient Precision-Scalable ConvNet Processor in 40-nm CMOS. IEEE J. Solid State Circuits 52(4): 903-914 (2017) - [c7]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum energy quantized neural networks. ACSSC 2017: 1921-1925 - [c6]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
DVAFS: Trading computational accuracy for energy through dynamic-voltage-accuracy-frequency-scaling. DATE 2017: 488-493 - [c5]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
14.5 Envision: A 0.26-to-10TOPS/W subword-parallel dynamic-voltage-accuracy-frequency-scalable Convolutional Neural Network processor in 28nm FDSOI. ISSCC 2017: 246-247 - [i3]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum Energy Quantized Neural Networks. CoRR abs/1711.00215 (2017) - 2016
- [c4]Bert Moons, Marian Verhelst:
A 0.3-2.6 TOPS/W precision-scalable processor for real-time large-scale ConvNets. VLSI Circuits 2016: 1-2 - [c3]Bert Moons, Bert De Brabandere, Luc Van Gool, Marian Verhelst:
Energy-efficient ConvNets through approximate computing. WACV 2016: 1-8 - [i2]Bert Moons, Bert De Brabandere, Luc Van Gool, Marian Verhelst:
Energy-Efficient ConvNets Through Approximate Computing. CoRR abs/1603.06777 (2016) - [i1]Bert Moons, Marian Verhelst:
A 0.3-2.6 TOPS/W Precision-Scalable Processor for Real-Time Large-Scale ConvNets. CoRR abs/1606.05094 (2016) - 2015
- [c2]Bert Moons, Marian Verhelst:
DVAS: Dynamic Voltage Accuracy Scaling for increased energy-efficiency in approximate computing. ISLPED 2015: 237-242 - 2014
- [j1]Bert Moons, Marian Verhelst:
Energy-Efficiency and Accuracy of Stochastic Computing Circuits in Emerging Technologies. IEEE J. Emerg. Sel. Topics Circuits Syst. 4(4): 475-486 (2014) - [c1]Bert Moons, Marian Verhelst:
Energy and accuracy in multi-stage stochastic computing. NEWCAS 2014: 197-200
Coauthor Index
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