Santiago Segarra

Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation

Prior-Informed Flow Matching for Graph Reconstruction

Adaptive node feature selection for graph neural networks

From Moments to Models: Graphon Mixture-Aware Mixup and Contrastive Learning

Boosting Adam-like Optimizers with Signal-to-Noise Ratio Guided Updates

Infinity Search: Approximate Vector Search with Projections on q-Metric Spaces

A Few Moments Please: Scalable Graphon Learning via Moment Matching

Repulsive Latent Score Distillation for Solving Inverse Problems