13 citations · 13 across the 5 of their papers we have counts for
5 papers
AQMP: Image compression through Adaptive Quadtree Refinement and Matching Pursuit with Hyperparameter Optimization
Franco Cerino, Emmanuel Tassone, Manuel Tiglio
We present AQMP, a novel image codec combining Adaptive Quadtree Refinement with Matching Pursuit. Unlike conventional Matching Pursuit methods that operate on fixed-size sub-image…
Building Machine Learning Challenges for Anomaly Detection in Science
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148
Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…
Hyperparameter optimization of hp-greedy reduced basis for gravitational wave surrogates
Franco Cerino, Andrés Diaz-Pace, Emmanuel Tassone +2
In a previous work we introduced, in the context of gravitational wave science, an initial study on an automated domain-decomposition approach for reduced basis through hp-greedy r…
An automated parameter domain decomposition approach for gravitational wave surrogates using hp-greedy refinement
Franco Cerino, J. Andrés Diaz-Pace, Manuel Tiglio
We introduce hp-greedy, a refinement approach for building gravitational wave surrogates as an extension of the standard reduced basis framework. Our proposal is data-driven, with…
Gravitational wave surrogates through automated machine learning
Damián Barsotti, Franco Cerino, Manuel Tiglio +1
We analyze a prospect for predicting gravitational waveforms from compact binaries based on automated machine learning (AutoML) from around a hundred different possible regression…