no code implementations • 22 Apr 2024 • Thomas Ortner, Horst Petschenig, Athanasios Vasilopoulos, Roland Renner, Špela Brglez, Thomas Limbacher, Enrique Piñero, Alejandro Linares Barranco, Angeliki Pantazi, Robert Legenstein
In this work, we pair L2L with in-memory computing NMHW based on phase-change memory devices to build efficient AI models that can rapidly adapt to new tasks.
no code implementations • 29 Sep 2023 • Matilde Tristany Farinha, Thomas Ortner, Giorgia Dellaferrera, Benjamin Grewe, Angeliki Pantazi
Artificial Neural Networks (ANNs) trained with Backpropagation (BP) excel in different daily tasks but have a dangerous vulnerability: inputs with small targeted perturbations, also known as adversarial samples, can drastically disrupt their performance.
no code implementations • 14 Jun 2023 • Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner
Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains.
no code implementations • 14 Apr 2023 • Yannick Schnider, Stanislaw Wozniak, Mathias Gehrig, Jules Lecomte, Axel von Arnim, Luca Benini, Davide Scaramuzza, Angeliki Pantazi
Optical flow provides information on relative motion that is an important component in many computer vision pipelines.
no code implementations • 11 Apr 2023 • Thomas Ortner, Lorenzo Pes, Joris Gentinetta, Charlotte Frenkel, Angeliki Pantazi
Recurrent neural networks trained with the backpropagation through time (BPTT) algorithm have led to astounding successes in various temporal tasks.
no code implementations • 13 Mar 2023 • Axel von Arnim, Jules Lecomte, Naima Elosegui Borras, Stanislaw Wozniak, Angeliki Pantazi
Temporal pattern recognition, depending on the technology, involves a trade-off between communication frequency, range and accurate tracking.
no code implementations • 23 Dec 2022 • Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner
Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence.
no code implementations • 28 Sep 2022 • Stanisław Woźniak, Hlynur Jónsson, Giovanni Cherubini, Angeliki Pantazi, Evangelos Eleftheriou
Visual oddity task was conceived as a universal ethnic-independent analytic intelligence test for humans.
no code implementations • 4 Oct 2021 • Thomas Bohnstingl, Ayush Garg, Stanisław Woźniak, George Saon, Evangelos Eleftheriou, Angeliki Pantazi
Automatic speech recognition (ASR) is a capability which enables a program to process human speech into a written form.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 23 Apr 2021 • Giorgia Dellaferrera, Stanislaw Wozniak, Giacomo Indiveri, Angeliki Pantazi, Evangelos Eleftheriou
Here, we propose a novel biologically inspired optimizer for artificial (ANNs) and spiking neural networks (SNNs) that incorporates key principles of synaptic integration observed in dendrites of cortical neurons: GRAPES (Group Responsibility for Adjusting the Propagation of Error Signals).
1 code implementation • 24 Jul 2020 • Thomas Bohnstingl, Stanisław Woźniak, Wolfgang Maass, Angeliki Pantazi, Evangelos Eleftheriou
For shallow networks, OSTL is gradient-equivalent to BPTT enabling for the first time online training of SNNs with BPTT-equivalent gradients.
1 code implementation • 17 Dec 2018 • Stanisław Woźniak, Angeliki Pantazi, Thomas Bohnstingl, Evangelos Eleftheriou
Neural networks have become the key technology of artificial intelligence and have contributed to breakthroughs in several machine learning tasks, primarily owing to advances in deep learning applied to Artificial Neural Networks (ANNs).