1.2k citations · 3.1k across the 36 of their papers we have counts for
5 papers · 1 filter
A Geometric Theory of Higher-Order Automatic Differentiation
Michael Betancourt
First-order automatic differentiation is a ubiquitous tool across statistics, machine learning, and computer science. Higher-order implementations of automatic differentiation, how…
Reassembling the English novel, 1789-1919
Allen Riddell, Michael Betancourt
The absence of an exhaustive bibliography of novels published in the British Isles and Ireland during the 19th century blocks several lines of research in sociologically-inclined l…
Validating Bayesian Inference Algorithms with Simulation-Based Calibration
Sean Talts, Michael Betancourt, Daniel Simpson +2
Verifying the correctness of Bayesian computation is challenging. This is especially true for complex models that are common in practice, as these require sophisticated model imple…
Calibrating Model-Based Inferences and Decisions
Michael Betancourt
As the frontiers of applied statistics progress through increasingly complex experiments we must exploit increasingly sophisticated inferential models to analyze the observations w…
On Symplectic Optimization
Michael Betancourt, Michael I. Jordan, Ashia C. Wilson
Accelerated gradient methods have had significant impact in machine learning -- in particular the theoretical side of machine learning -- due to their ability to achieve oracle low…