Conditioning the Gaussian latent or output distribution of a deep generative model on a linear equality constraint, with the conditional mean as the gradient proxy, enforces the constraint exactly and improves generation quality over post-hoc projection baselines.
Spectral temporal graph neural network for multivariate time-series forecasting
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
-
Deep Generative Models with Hard Linear Equality Constraints
Conditioning the Gaussian latent or output distribution of a deep generative model on a linear equality constraint, with the conditional mean as the gradient proxy, enforces the constraint exactly and improves generation quality over post-hoc projection baselines.