2 citations · 2 across the 5 of their papers we have counts for
5 papers
Evaluating Loss Functions in Differentiable Out-of-Domain Sound-Matching with Partial Parameter Distance
Amir Salimi, Daniel Penner, Kalvin Eng +2
In out-of-domain (OOD) sound-matching, a synthesizer is optimized to mimic a sound it did not generate. OOD evaluation of loss functions is underexplored in part because the standa…
Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction
Jie Lin, Weijie Sun, Sunil V. Kalmady +4
Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, population, and measurement di…
Evaluating Sound Similarity Metrics for Differentiable, Iterative Sound-Matching
Amir Salimi, Abram Hindle, Osmar R. Zaiane
Manual sound design with a synthesizer is inherently iterative: an artist compares the synthesized output to a mental target, adjusts parameters, and repeats until satisfied. Itera…
Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data
Vikhyat Agrawal, Sunil Vasu Kalmady, Venkataseetharam Manoj Malipeddi +6
This research paper explores ways to apply Federated Learning (FL) and Differential Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study learns a mul…
Exploring Best Practices for ECG Pre-Processing in Machine Learning
Amir Salimi, Sunil Vasu Kalmady, Abram Hindle +2
In this work we search for best practices in pre-processing of Electrocardiogram (ECG) signals in order to train better classifiers for the diagnosis of heart conditions. State of…