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cs.LG2025
Self-Supervised Graph Learning via Spectral Bootstrapping and Laplacian-Based Augmentations
Lorenzo Bini, Stephane Marchand-Maillet
We present LaplaceGNN, a novel self-supervised graph learning framework that bypasses the need for negative sampling by leveraging spectral bootstrapping techniques. Our method int…
cs.LG2025
LapDDPM: Spectral Perturbation Diffusion for Robust Single-Cell Manifold Generation
Lorenzo Bini, Stephane Marchand-Maillet
Generating high-fidelity and biologically plausible synthetic single-cell RNA sequencing (scRNA-seq) data is a critical challenge in computational biology, driven by the need to mo…