12 citations · 67 across the 40 of their papers we have counts for
4 papers · 1 filter
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan +1
Current Deep Network (DN) visualization and interpretability methods rely heavily on data space visualizations such as scoring which dimensions of the data are responsible for thei…
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values
Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk
We present Polarity Sampling, a theoretically justified plug-and-play method for controlling the generation quality and diversity of pre-trained deep generative networks DGNs). Lev…
NeuroView: Explainable Deep Network Decision Making
CJ Barberan, Randall Balestriero, Richard G. Baraniuk
Deep neural networks (DNs) provide superhuman performance in numerous computer vision tasks, yet it remains unclear exactly which of a DN's units contribute to a particular decisio…
Interpretable Image Clustering via Diffeomorphism-Aware K-Means
Romain Cosentino, Randall Balestriero, Yanis Bahroun +3
We design an interpretable clustering algorithm aware of the nonlinear structure of image manifolds. Our approach leverages the interpretability of -means applied in the image s…