Thomas Bohnstingl
Thomas Bohnstingl
PhD Student at IBM Research Zurich and Graz University of Technology
Verified email at student.tugraz.at
Title
Cited by
Cited by
Year
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
25*2020
Neuromorphic hardware learns to learn
T Bohnstingl, F Scherr, C Pehle, K Meier, W Maass
Frontiers in neuroscience 13, 483, 2019
192019
Online spatio-temporal learning in deep neural networks
T Bohnstingl, S Woźniak, W Maass, A Pantazi, E Eleftheriou
arXiv preprint arXiv:2007.12723, 2020
32020
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
12021
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
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
2020
Biologically Inspired dynamics Enhance deep Learning
S Woźniak, T Bohnstingl, A Pantazi
Brain-inspired Computing, 8, 0
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Articles 1–7