24 citations · 40 across the 6 of their papers we have counts for
6 papers
Distance preservation in state-space methods for detecting causal interactions in dynamical systems
Matthew O'Shaughnessy, Mark Davenport, Christopher Rozell
We analyze the popular ``state-space'' class of algorithms for detecting casual interaction in coupled dynamical systems. These algorithms are often justified by Takens' embedding…
PrefGen: Preference Guided Image Generation with Relative Attributes
Alec Helbling, Christopher J. Rozell, Matthew O'Shaughnessy +1
Deep generative models have the capacity to render high fidelity images of content like human faces. Recently, there has been substantial progress in conditionally generating image…
Five policy uses of algorithmic transparency and explainability
Matthew O'Shaughnessy
The notion that algorithmic systems should be "transparent" and "explainable" is common in the many statements of consensus principles developed by governments, companies, and advo…
Oracle Guided Image Synthesis with Relative Queries
Alec Helbling, Christopher John Rozell, Matthew O'Shaughnessy +1
Isolating and controlling specific features in the outputs of generative models in a user-friendly way is a difficult and open-ended problem. We develop techniques that allow an or…
Generative causal explanations of black-box classifiers
Matthew O'Shaughnessy, Gregory Canal, Marissa Connor +2
We develop a method for generating causal post-hoc explanations of black-box classifiers based on a learned low-dimensional representation of the data. The explanation is causal in…
Sparse Bayesian Learning with Dynamic Filtering for Inference of Time-Varying Sparse Signals
Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
Many signal processing applications require estimation of time-varying sparse signals, potentially with the knowledge of an imperfect dynamics model. In this paper, we propose an a…