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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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6 results for “iEEG”

One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations: Local Binary Patterns with Hyperdimensional Computingeess.SP

Efficient binarized algorithm detects seizures from iEEG with one-shot learning.

problem Detecting seizures from iEEG data efficiently and accurately.

method Combines local binary patterns with hyperdimensional computing for end-to-end binary operations.

result Algorithm learns from one or two seizures and generalizes on 27 further seizures.

iEEG seizure detection one-shot learning local binary patterns hyperdimensional computing

2018-09-06abs ↗pdf ↗

Convolutional Neural Networks for Epileptic Seizure Predictioncs.LG

CNN predicts epileptic seizures from iEEG signals.

problem Accurately forecasting epileptic seizures to reduce patient uncertainty.

method Used a CNN for seizure prediction without hand-crafted features.

result CNN models outperformed previous methods on public datasets.

Epilepsy Seizure prediction Convolutional Neural Networks Intracranial EEG Binary classification

2018-11-02abs ↗pdf ↗

Modeling the Complex Dynamics and Changing Correlations of Epileptic Eventsstat.ML

Patients with epilepsy can manifest short, sub-clinical epileptic "bursts" in addition to full-blown clinical seizures. We believe the relationship between these two classes of events---something not previously studied quantitatively---could yield important insights into the nature and intrinsic dynamics of seizures. A…

2014-02-27abs ↗pdf ↗

Node-Centric Graph Learning from Data for Brain State Identificationcs.LG

Graph learning method improves brain state classification.

problem Classifying brain states from iEEG signals.

method Representation learning on graphs for time-varying brain networks.

result 9.13% improvement in AUC for seizure vs. non-seizure classification.

graph learning representation learning brain networks iEEG signals seizure detection

2020-11-04abs ↗pdf ↗

A Hierarchical Dirichlet Process Model with Multiple Levels of Clustering for Human EEG Seizure Modelingstat.AP

Driven by the multi-level structure of human intracranial electroencephalogram (iEEG) recordings of epileptic seizures, we introduce a new variant of a hierarchical Dirichlet Process---the multi-level clustering hierarchical Dirichlet Process (MLC-HDP)---that simultaneously clusters datasets on multiple levels. Our sei…

2012-06-18abs ↗pdf ↗

Divergence Phase Index: A Riesz-Transform Framework for Multidimensional Phase Difference Analysisstat.ML

DPI quantifies phase differences in 1D and multidimensional signals using Riesz transform.

problem Quantifying phase differences in signals of varying dimensions.

method Riesz transform framework for harmonic analysis.

result DPI detects hypersynchronization and subtle changes in images and artworks.

phase difference Riesz transform multidimensional signals hypersynchronization image analysis

2025-10-06abs ↗pdf ↗