A Bayesian method embeds linear equality constraints into variational inference for neural networks, yielding reduced credible intervals and fewer constraint violations on a single-particle battery model versus standard variational Bayesian neural networks.
Derek Hansen, Danielle C
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Learning with Embedded Linear Equality Constraints via Variational Bayesian Inference
A Bayesian method embeds linear equality constraints into variational inference for neural networks, yielding reduced credible intervals and fewer constraint violations on a single-particle battery model versus standard variational Bayesian neural networks.