32 citations · 71 across the 11 of their papers we have counts for
5 papers · 1 filter
Flatness and Gradient Alignment Are Both Necessary: Spectral-Aware Gradient-Aligned Exploration for Multi-Distribution Learning
Aristotelis Ballas, Christos Diou
Sharpness-aware and gradient-alignment methods have been shown to improve generalization, however each family of methods targets a single geometric property of the loss landscape,…
Gradient-Guided Annealing for Domain Generalization
Aristotelis Ballas, Christos Diou
Domain Generalization (DG) research has gained considerable traction as of late, since the ability to generalize to unseen data distributions is a requirement that eludes even stat…
Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning
Aristotelis Ballas, Vasileios Papapanagiotou, Christos Diou
Despite recent advancements in deep learning, its application in real-world medical settings, such as phonocardiogram (PCG) classification, remains limited. A significant barrier i…
Listen2YourHeart: A Self-Supervised Approach for Detecting Murmur in Heart-Beat Sounds
Aristotelis Ballas, Vasileios Papapanagiotou, Anastasios Delopoulos +1
Heart murmurs are abnormal sounds present in heartbeats, caused by turbulent blood flow through the heart. The PhysioNet 2022 challenge targets automatic detection of murmur from a…
A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks
Aristotelis Ballas, Christos Diou
Deep Learning systems have achieved great success in the past few years, even surpassing human intelligence in several cases. As of late, they have also established themselves in t…