67 citations · 112 across the 11 of their papers we have counts for
16 papers
Design of Unmanned Air Vehicles Using Transformer Surrogate Models
Adam D. Cobb, Anirban Roy, Daniel Elenius +1
Computer-aided design (CAD) is a promising new area for the application of artificial intelligence (AI) and machine learning (ML). The current practice of design of cyber-physical…
Principal Manifold Flows
Edmond Cunningham, Adam Cobb, Susmit Jha
Normalizing flows map an independent set of latent variables to their samples using a bijective transformation. Despite the exact correspondence between samples and latent variable…
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning
Meet P. Vadera, Adam D. Cobb, Brian Jalaian +1
Bayesian methods hold significant promise for improving the uncertainty quantification ability and robustness of deep neural network models. Recent research has seen the investigat…
HumBugDB: A Large-scale Acoustic Mosquito Dataset
Ivan Kiskin, Marianne Sinka, Adam D. Cobb +13
This paper presents the first large-scale multi-species dataset of acoustic recordings of mosquitoes tracked continuously in free flight. We present 20 hours of audio recordings th…
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
Vyacheslav Kungurtsev, Adam Cobb, Tara Javidi +1
Federated learning performed by a decentralized networks of agents is becoming increasingly important with the prevalence of embedded software on autonomous devices. Bayesian appro…
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…