2 citations · 2 across the 3 of their papers we have counts for
3 papers
Epileptic seizure forecasting with long short-term memory (LSTM) neural networks
Daniel E. Payne, Jordan D. Chambers, Anthony Burkitt +4
Objective: Forecasting epileptic seizures can reduce uncertainty for patients and allow preventative actions. While many models can predict the occurrence of seizures from features…
Path Signatures for Seizure Forecasting
Jonas F. Haderlein, Andre D. H. Peterson, Parvin Zarei Eskikand +4
Predicting future system behaviour from past observed behaviour (time series) is fundamental to science and engineering. In computational neuroscience, the prediction of future epi…
Brain Model State Space Reconstruction Using an LSTM Neural Network
Yueyang Liu, Artemio Soto-Breceda, Yun Zhao +5
Objective Kalman filtering has previously been applied to track neural model states and parameters, particularly at the scale relevant to EEG. However, this approach lacks a reliab…