3 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Thermodynamic Bayesian Inference
Maxwell Aifer, Samuel Duffield, Kaelan Donatella +6
A fully Bayesian treatment of complicated predictive models (such as deep neural networks) would enable rigorous uncertainty quantification and the automation of higher-level tasks…
Scalable Bayesian Learning with posteriors
Samuel Duffield, Kaelan Donatella, Johnathan Chiu +2
Although theoretically compelling, Bayesian learning with modern machine learning models is computationally challenging since it requires approximating a high dimensional posterior…
Thermodynamic Natural Gradient Descent
Kaelan Donatella, Samuel Duffield, Maxwell Aifer +3
Second-order training methods have better convergence properties than gradient descent but are rarely used in practice for large-scale training due to their computational overhead.…