7 citations · 8 across the 4 of their papers we have counts for
6 papers
Task-driven Processing with Coarse-to-Fine Glimpse-based Active Perception
Oleh Kolner, Thomas Ortner, Stanisław Woźniak +1
State-of-the-art vision models process images in their entirety, lacking the ability to selectively zoom in on relevant regions. This limitation is particularly acute in scenarios…
FlowState: Sampling-Rate-Equivariant Time-Series Forecasting
Lars Graf, Thomas Ortner, Stanisław Woźniak +1
Existing time series foundation models (TSFMs), often based on transformer variants, lack adaptability to different sampling rates, struggle with generalization across varying cont…
An Exact Mapping From ReLU Networks to Spiking Neural Networks
Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec +3
Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks t…
On the visual analytic intelligence of neural networks
Stanisław Woźniak, Hlynur Jónsson, Giovanni Cherubini +2
Visual oddity task was conceived as a universal ethnic-independent analytic intelligence test for humans. Advancements in artificial intelligence led to important breakthroughs, ye…
Towards efficient end-to-end speech recognition with biologically-inspired neural networks
Thomas Bohnstingl, Ayush Garg, Stanisław Woźniak +3
Automatic speech recognition (ASR) is a capability which enables a program to process human speech into a written form. Recent developments in artificial intelligence (AI) have led…
Online Spatio-Temporal Learning in Deep Neural Networks
Thomas Bohnstingl, Stanisław Woźniak, Wolfgang Maass +2
Biological neural networks are equipped with an inherent capability to continuously adapt through online learning. This aspect remains in stark contrast to learning with error back…