Thomas Bohnstingl
Thomas Bohnstingl
PhD Student at IBM Research Zurich and Graz University of Technology
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Cited by
Cited by
Deep learning incorporating biologically inspired neural dynamics and in-memory computing
S Woźniak, A Pantazi, T Bohnstingl, E Eleftheriou
Nature Machine Intelligence 2 (6), 325-336, 2020
Neuromorphic hardware learns to learn
T Bohnstingl, F Scherr, C Pehle, K Meier, W Maass
Frontiers in neuroscience 13, 483, 2019
Online spatio-temporal learning in deep neural networks
T Bohnstingl, S Woźniak, W Maass, A Pantazi, E Eleftheriou
arXiv preprint arXiv:2007.12723, 2020
Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation
RL Bruce, SG Sarwat, I Boybat, CW Cheng, W Kim, SR Nandakumar, ...
2021 IEEE International Reliability Physics Symposium (IRPS), 1-6, 2021
Neuromorphic device with crossbar array structure storing both weights and neuronal states of neural networks
T Bohnstingl, A Pantazi, ES Eleftheriou
US Patent App. 16/685,045, 2021
Accelerating Spiking Neural Networks using Memristive Crossbar Arrays
T Bohnstingl, A Pantazi, E Eleftheriou
2020 27th IEEE International Conference on Electronics, Circuits and Systems …, 2020
Biologically Inspired dynamics Enhance deep Learning
S Woźniak, T Bohnstingl, A Pantazi
Brain-inspired Computing, 8, 0
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