67 citations · 233 across the 19 of their papers we have counts for
5 papers · 1 filter
Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization
Subhodip Biswas, Adam D Cobb, Andreea Sistrunk +2
In this paper, we propose a surrogate-assisted evolutionary algorithm (EA) for hyperparameter optimization of machine learning (ML) models. The proposed STEADE model initially esti…
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting
Adam D. Cobb, Brian Jalaian
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) approach that exhibits favourable exploration properties in high-dimensional models such as neural networks. Unfo…
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks
Meet P. Vadera, Adam D. Cobb, Brian Jalaian +1
While deep learning methods continue to improve in predictive accuracy on a wide range of application domains, significant issues remain with other aspects of their performance inc…
Accurate Machine Learning Atmospheric Retrieval via a Neural Network Surrogate Model for Radiative Transfer
Michael D. Himes, Joseph Harrington, Adam D. Cobb +8
Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach…
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset
Ivan Kiskin, Adam D. Cobb, Lawrence Wang +1
Mosquitoes are the only known vector of malaria, which leads to hundreds of thousands of deaths each year. Understanding the number and location of potential mosquito vectors is of…