Towards efficient end-to-end speech recognition with biologically-inspired neural networksThomas BohnstinglAyush Garget al.2021NeurIPS 2021
High-performance deep spiking neural networks with 0.3 spikes per neuronAna StanojevicStanisław Woźniaket al.2024Nature Communications
Deep learning incorporating biologically inspired neural dynamics and in-memory computingStanisław WoźniakAngeliki Pantaziet al.2020Nature Machine Intelligence
Approximating Relu Networks by Single-Spike ComputationAna StanojevicEvangelos Eleftheriouet al.2022ICIP 2022
Unsupervised Learning Using Phase-Change Synapses and Complementary PatternsSeverin SidlerAngeliki Pantaziet al.2017ICANN 2017
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural NetworksSidney TsaiPritish Narayananet al.2023ISCAS 2023
Efficient biologically-inspired online learning alternatives to BPTTThomas BohnstinglStanisław Woźniaket al.2024ICNCE 2024
Neuromorphic Optical Flow and Real-time Implementation with Event CamerasYannick SchniderStanisław Woźniaket al.2023CVPR 2023
Are training trajectories of deep single-spike and deep ReLU network equivalent?Ana StanojevicStanisław Woźniaket al.2023arXiv
An exact mapping from ReLU networks to spiking neural networksAna StanojevicStanisław Woźniaket al.2022arXiv