44 citations · 52 across the 4 of their papers we have counts for
5 papers
PI-NOMT: Physics-Informed Neural Optimal Mass Transport for Brain Fluid Dynamics
Mehmet Emin Acar, Vahit Bugra Yesilkaynak, Helene Benveniste +1
Recovering hidden transport mechanisms from sparse spatiotemporal observations is a fundamental inverse problem in scientific machine learning. In brain tracer imaging, dynamic con…
UniMLR: Modeling Implicit Class Significance for Multi-Label Ranking
V. Bugra Yesilkaynak, Emine Dari, Alican Mertan +1
Existing multi-label ranking (MLR) frameworks only exploit information deduced from the bipartition of labels into positive and negative sets. Therefore, they do not benefit from r…
RLSEP: Learning Label Ranks for Multi-label Classification
Emine Dari, V. Bugra Yesilkaynak, Alican Mertan +1
Multi-label ranking maps instances to a ranked set of predicted labels from multiple possible classes. The ranking approach for multi-label learning problems received attention for…
Detecting Visual Design Principles in Art and Architecture through Deep Convolutional Neural Networks
Gozdenur Demir, Asli Cekmis, Vahit Bugra Yesilkaynak +1
Visual design is associated with the use of some basic design elements and principles. Those are applied by the designers in the various disciplines for aesthetic purposes, relying…
EfficientSeg: An Efficient Semantic Segmentation Network
Vahit Bugra Yesilkaynak, Yusuf H. Sahin, Gozde Unal
Deep neural network training without pre-trained weights and few data is shown to need more training iterations. It is also known that, deeper models are more successful than their…