42 citations · 67 across the 11 of their papers we have counts for
5 papers · 1 filter
Personalization on a Budget: Minimally-Labeled Continual Learning for Resource-Efficient Seizure Detection
Amirhossein Shahbazinia, Jonathan Dan, Jose A. Miranda +2
Objective: Epilepsy, a prevalent neurological disease, demands careful diagnosis and continuous care. Seizure detection remains challenging, as current clinical practice relies on…
Time series saliency maps: explaining models across multiple domains
Christodoulos Kechris, Jonathan Dan, David Atienza
Traditional saliency map methods, popularized in computer vision, highlight individual points (pixels) of the input that contribute the most to the model's output. However, in time…
Don't Think It Twice: Exploit Shift Invariance for Efficient Online Streaming Inference of CNNs
Christodoulos Kechris, Jonathan Dan, Jose Miranda +1
Deep learning time-series processing often relies on convolutional neural networks with overlapping windows. This overlap allows the network to produce an output faster than the wi…
DC is all you need: describing ReLU from a signal processing standpoint
Christodoulos Kechris, Jonathan Dan, Jose Miranda +1
Non-linear activation functions are crucial in Convolutional Neural Networks. However, until now they have not been well described in the frequency domain. In this work, we study t…
How to Count Coughs: An Event-Based Framework for Evaluating Automatic Cough Detection Algorithm Performance
Lara Orlandic, Jonathan Dan, Jerome Thevenot +3
Chronic cough disorders are widespread and challenging to assess because they rely on subjective patient questionnaires about cough frequency. Wearable devices running Machine Lear…