2 papers
cs.LG2026
Supervised Graph Contrastive Learning for Gene Regulatory Networks
Sho Oshima, Yuji Okamoto, Taisei Tosaki +1
Graph Contrastive Learning (GCL) is a powerful self-supervised learning framework that performs data augmentation through graph perturbations, with growing applications in the anal…
cs.LG2024
Learning Deep Dissipative Dynamics
Yuji Okamoto, Ryosuke Kojima
This study challenges strictly guaranteeing ``dissipativity'' of a dynamical system represented by neural networks learned from given time-series data. Dissipativity is a crucial i…