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cs.LG2026
Identifying Information from Observations with Uncertainty and Novelty
Derek S. Prijatelj, Timothy J. Ireland, Walter J. Scheirer
A machine that learns a task from observations must encounter and process uncertainty and novelty, especially when it is to maintain performance when observing new information and…
cs.LG2024
This Probably Looks Exactly Like That: An Invertible Prototypical Network
Zachariah Carmichael, Timothy Redgrave, Daniel Gonzalez Cedre +1
We combine concept-based neural networks with generative, flow-based classifiers into a novel, intrinsically explainable, exactly invertible approach to supervised learning. Protot…