Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
The episode discusses 'Beliefs Beyond Posteriors,' a paper introducing the SCROLL estimator for Bayesian Neural Networks. Hosts discuss how this method uses a shared-cavity and free-routing approach to make powerful Bayesian techniques scalable, efficient, and applicable to diverse real-world data.