452 citations · 870 across the 33 of their papers we have counts for
34 papers
Capturing Humans' Mental Models of AI: An Item Response Theory Approach
Markelle Kelly, Aakriti Kumar, Padhraic Smyth +1
Improving our understanding of how humans perceive AI teammates is an important foundation for our general understanding of human-AI teams. Extending relevant work from cognitive s…
Functional Flow Matching
Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth
We propose Functional Flow Matching (FFM), a function-space generative model that generalizes the recently-introduced Flow Matching model to operate in infinite-dimensional spaces.…
Diffusion Generative Models in Infinite Dimensions
Gavin Kerrigan, Justin Ley, Padhraic Smyth
Diffusion generative models have recently been applied to domains where the available data can be seen as a discretization of an underlying function, such as audio signals or time…
Predictive Querying for Autoregressive Neural Sequence Models
Alex Boyd, Sam Showalter, Stephan Mandt +1
In reasoning about sequential events it is natural to pose probabilistic queries such as "when will event A occur next" or "what is the probability of A occurring before B", with a…
Variable-Based Calibration for Machine Learning Classifiers
Markelle Kelly, Padhraic Smyth
The deployment of machine learning classifiers in high-stakes domains requires well-calibrated confidence scores for model predictions. In this paper we introduce the notion of var…
Fair Generalized Linear Models with a Convex Penalty
Hyungrok Do, Preston Putzel, Axel Martin +2
Despite recent advances in algorithmic fairness, methodologies for achieving fairness with generalized linear models (GLMs) have yet to be explored in general, despite GLMs being w…