no code implementations • 10 Nov 2021 • Chuteng Zhou, Fernando Garcia Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough
We also describe AON-CiM, a programmable, minimal-area phase-change memory (PCM) analog CiM accelerator, with a novel layer-serial approach to remove the cost of complex interconnects associated with a fully-pipelined design.
1 code implementation • 6 Oct 2021 • Julian Büchel, Gregor Lenz, Yalun Hu, Sadique Sheik, Martino Sorbaro
Event-based dynamic vision sensors provide very sparse output in the form of spikes, which makes them suitable for low-power applications.
no code implementations • ICLR 2022 • Julian Büchel, Fynn Firouz Faber, Dylan Richard Muir
We present a new network training algorithm that attacks network parameters during training, and promotes robust performance during inference in the face of random parameter variation.
2 code implementations • 9 Jun 2021 • Julian Büchel, Fynn Faber, Dylan R. Muir
We present a new adversarial network optimisation algorithm that attacks network parameters during training, and promotes robust performance during inference in the face of parameter variation.
no code implementations • 12 Feb 2021 • Julian Büchel, Dmitrii Zendrikov, Sergio Solinas, Giacomo Indiveri, Dylan R. Muir
Our method provides robust deployment of pre-trained networks on mixed-signal neuromorphic hardware, without requiring per-device training or calibration.
1 code implementation • 27 Oct 2020 • Julian Büchel, Jonathan Kakon, Michel Perez, Giacomo Indiveri
Our proposed method paves the way towards a system-level implementation of tightly balanced networks on analog mixed-signal neuromorphic hardware.
no code implementations • 4 Dec 2018 • Julian Büchel, Okan Ersoy
We used the Ladder Network [Rasmus et al. (2015)] to perform Hyperspectral Image Classification in a semi-supervised setting.