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cs.LG2025
DIVIDE: A Framework for Learning from Independent Multi-Mechanism Data Using Deep Encoders and Gaussian Processes
Vivek Chawla, Boris Slautin, Utkarsh Pratiush +2
Scientific datasets often arise from multiple independent mechanisms such as spatial, categorical or structural effects, whose combined influence obscures their individual contribu…
cs.LG2025
Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE Model
Boris N. Slautin, Utkarsh Pratiush, Doru C. Lupascu +2
We introduce a Deep Kernel Learning Variational Autoencoder (VAE-DKL) framework that integrates the generative power of a Variational Autoencoder (VAE) with the predictive nature o…