1 citations · 1 across the 4 of their papers we have counts for
5 papers
Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models
Aleksandar Terzić, Francesco Carzaniga, Nicolas Menet +4
State-space models (SSMs) face a fundamental trade-off between efficiency and expressivity that is mainly dictated by the structure of the model's transition matrix. Unstructured t…
A Composable Channel-Adaptive Architecture for Seizure Classification
Francesco Carzaniga, Michael Hersche, Kaspar Schindler +1
Objective: We develop a channel-adaptive (CA) architecture that seamlessly processes multi-variate time-series with an arbitrary number of channels, and in particular intracranial…
A foundation model with multi-variate parallel attention to generate neuronal activity
Francesco Carzaniga, Michael Hersche, Abu Sebastian +2
Learning from multi-variate time-series with heterogeneous channel configurations remains a fundamental challenge for deep neural networks, particularly in clinical domains such as…
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG
Francesco Stefano Carzaniga, Gary Tom Hoppeler, Michael Hersche +2
All data modalities are not created equal, even when the signal they measure comes from the same source. In the case of the brain, two of the most important data modalities are the…
A Theoretical Framework for Target Propagation
Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens +2
The success of deep learning, a brain-inspired form of AI, has sparked interest in understanding how the brain could similarly learn across multiple layers of neurons. However, the…