A conditional graph diffusion model with Laplacian positional encodings and spectral adversarial edge-weight perturbations reports improved MMD and Wasserstein metrics on four scRNA-seq datasets.
Graph contrastive learning with stable and scalable spectral encoding
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
LapDDPM: A Conditional Graph Diffusion Model for scRNA-seq Generation with Spectral Adversarial Perturbations
A conditional graph diffusion model with Laplacian positional encodings and spectral adversarial edge-weight perturbations reports improved MMD and Wasserstein metrics on four scRNA-seq datasets.