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Found 4 papers, 0 papers with code
Field-of-View Extension for Diffusion MRI via Deep Generative Models
We hypothesize that the imputed image with complete FOV can improve the whole-brain tractography for corrupted data with incomplete FOV.
Generalized Linear Tree Space Nearest Neighbor
We present a novel method of stacking decision trees by projection into an ordered time split out-of-fold (OOF) one nearest neighbor (1NN) space.
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
We develop and study multicalibration as a new measure of fairness in machine learning that aims to mitigate inadvertent or malicious discrimination that is introduced at training time (even from ground truth data).
Developing Quantum Annealer Driven Data Discovery
Through these experiments, we provide unique insights into the state of quantum ML via boosting and the use of quantum annealing hardware that are valuable to institutions interested in applying QA to problems in ML and beyond.
