RobustSeiz: An Open-Source Framework for Benchmarking the Robustness of EEG Seizure Detection Models

arXiv:2609.04007 · cs.LG, eess.SP · Submitted 2026-09-03 · Read on arXiv

cs.LG, eess.SP

Submitted: 2026-09-03

Updated: 2026-09-03

Code: https://github.com/iMohammad97/RobustSeiz

Terminology

• Robustness — 47× in this paper · explained in 5 episodes
• Accuracy — 27× in this paper · explained in 1 episode
• Monte Carlo dropout — 19× in this paper · explained in 2 episodes
• Benchmarking — 6× in this paper · explained in 3 episodes
• Quantization — 5× in this paper · explained in 12 episodes
• Distribution Shift — 4× in this paper · explained in 5 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Adversarial Attacks — 3× in this paper · explained in 1 episode
• International League Against Epilepsy — 3× in this paper
• Latent Space — 3× in this paper · explained in 7 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• European Data Format — 2× in this paper
• External Validation — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• International Federation of Clinical Neurophysiology — 2× in this paper
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fast Gradient Sign Method — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• International Conference on Learning Representations — 1× in this paper
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Projected Gradient Descent — 1× in this paper
• Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks