activity
20202026
most citedQ-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine Interfaces

7 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NI2026

Self-evolving network verifiers

Ioannis Protogeros, Tibor Schneider, Laurent Vanbever

Symbolic network verifiers can reason about correctness across vast spaces of routing inputs and failures, but only for the protocols and features an expert has encoded by hand. Cr…

cs.NI2025

The Effects of iBGP Convergence

Roland Schmid, Tibor Schneider, Georgia Fragkouli +1

Analyzing violations of forwarding properties is a classic networking problem. However, existing work is either tailored to the steady state -- and not to transient states during i…

eess.SP2021

Sub-100uW Multispectral Riemannian Classification for EEG-based Brain--Machine Interfaces

Xiaying Wang, Lukas Cavigelli, Tibor Schneider +1

Motor imagery brain--machine interfaces enable us to control machines by merely thinking of performing a motor action. Practical use cases require a wearable solution where the cla…

eess.SP2021

Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain--Machine Interfaces

Xiaying Wang, Tibor Schneider, Michael Hersche +2

With Motor-Imagery (MI) Brain--Machine Interfaces (BMIs) we may control machines by merely thinking of performing a motor action. Practical use cases require a wearable solution wh…

eess.SP2020★ 7 cited

Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain--Machine Interfaces

Tibor Schneider, Xiaying Wang, Michael Hersche +2

Motor-Imagery Brain--Machine Interfaces (MI-BMIs)promise direct and accessible communication between human brains and machines by analyzing brain activities recorded with Electroen…