Applied Mathematics
Estimating a manifold from noisy samples
Learning Graph Inverse Problems with Geometric Neural Networks
Learning from Highly Correlated Features using Graph Total Variation
Latent Space Approaches to Subtyping in Oncology Trials
Stable singularity detection from low-resolution data
Spectral methods for unsupervised ensemble learning and latent variable models
Deep Spectral Graph Matching
A fluctuating boundary integral method for Brownian suspensions.
Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering
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