101 citations · 151 across the 18 of their papers we have counts for
8 papers · 1 filter
NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
Anwar Said, Roza G. Bayrak, Tyler Derr +4
Machine learning provides a valuable tool for analyzing high-dimensional functional neuroimaging data, and is proving effective in predicting various neurological conditions, psych…
Harmonization and the Worst Scanner Syndrome
Daniel Moyer, Polina Golland
We show that for a wide class of harmonization/domain-invariance schemes several undesirable properties are unavoidable. If a predictive machine is made invariant to a set of domai…
DEMI: Discriminative Estimator of Mutual Information
Ruizhi Liao, Daniel Moyer, Polina Golland +1
Estimating mutual information between continuous random variables is often intractable and extremely challenging for high-dimensional data. Recent progress has leveraged neural net…
Discovery and Separation of Features for Invariant Representation Learning
Ayush Jaiswal, Rob Brekelmans, Daniel Moyer +3
Supervised machine learning models often associate irrelevant nuisance factors with the prediction target, which hurts generalization. We propose a framework for training robust ne…
Invariant Representations through Adversarial Forgetting
Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg +2
We propose a novel approach to achieving invariance for deep neural networks in the form of inducing amnesia to unwanted factors of data through a new adversarial forgetting mechan…
Efficient Covariance Estimation from Temporal Data
Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian +2
Estimating the covariance structure of multivariate time series is a fundamental problem with a wide-range of real-world applications -- from financial modeling to fMRI analysis. D…