Gromov-Wasserstein distance has found many applications in machine learn...
Multimodal learning models have become increasingly important as they su...
Alzheimer's Disease (AD) is the most common neurodegenerative disorder w...
Optimal transport (OT) compares probability distributions by computing a...
We present a joint graph convolution-image convolution neural network as...
Computational methods that predict differential gene expression from his...
One of the fundamental tasks in understanding genomics is the problem of...
The past decade has seen a revolution in genomic technologies that enabl...
String Kernel (SK) techniques, especially those using gapped k-mers as
f...
When analyzing the genome, researchers have discovered that proteins bin...
Deep neural network (DNN) models have recently obtained state-of-the-art...
Identifying context-specific entity networks from aggregated data is an
...