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Found 8 papers, 1 papers with code
A Finite-Horizon Approach to Active Level Set Estimation
We present a finite-horizon search procedure to perform LSE in one dimension while optimally balancing both the final estimation error and the distance traveled for a fixed number of samples.
Learning High-Dimensional Nonparametric Differential Equations via Multivariate Occupation Kernel Functions
Learning a nonparametric system of ordinary differential equations (ODEs) from $n$ trajectory snapshots in a $d$-dimensional state space requires learning $d$ functions of $d$ variables.
Learning Riemannian metric for disease progression modeling
Specifically, we learn the metric as the push-forward of the Euclidean metric by a diffeomorphism.
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease.
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held on December 8, 2018 in Montreal, Canada.
Gaussian Processes with Context-Supported Priors for Active Object Localization
Next, we use a Gaussian Process to model this offset response signal over the search space of the target.
Non-Adaptive Policies for 20 Questions Target Localization
The problem of target localization with noise is addressed.
Active Testing for Face Detection and Localization
We provide a novel search technique, which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images.
