Adam Cobb
Adam Cobb
Senior Research Engineer, Southwest Research Institute
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
Bayesopt adversarial attack
B Ru, A Cobb, A Blaas, Y Gal
International Conference on Learning Representations, 2019
An ensemble of bayesian neural networks for exoplanetary atmospheric retrieval
AD Cobb, MD Himes, F Soboczenski, S Zorzan, MD O’Beirne, AG Baydin, ...
The astronomical journal 158 (1), 33, 2019
Loss-calibrated approximate inference in Bayesian neural networks
AD Cobb, SJ Roberts, Y Gal
arXiv preprint arXiv:1805.03901, 2018
Torsional guided wave attenuation in piping from coating, temperature, and large-area corrosion
AC Cobb, H Kwun, L Caseres, G Janega
NDT & E International 47, 163-170, 2012
A comparison of feature-based classifiers for ultrasonic structural health monitoring
JE Michaels, AC Cobb, TE Michaels
Health Monitoring and Smart Nondestructive Evaluation of Structural and …, 2004
Model-assisted probability of detection for ultrasonic structural health monitoring
C Adam, J Fisher, JE Michaels
Proceedings of the 4th European-American Workshop on Reliability of NDE …, 2009
An automated time–frequency approach for ultrasonic monitoring of fastener hole cracks
AC Cobb, JE Michaels, TE Michaels
NDT & E International 40 (7), 525-536, 2007
Review of magnetostrictive transducers (MsT) utilizing reversed Wiedemann effect
S Vinogradov, A Cobb, G Light
AIP Conference Proceedings 1806 (1), 020008, 2017
Self‐Calibrating Ultrasonic Methods for In‐Situ Monitoring of Fatigue Crack Progression
JE Michaels, TE Michaels, B Mi, AC Cobb, DM Stobbe
AIP Conference Proceedings 760 (1), 1765-1772, 2005
Ultrasonic structural health monitoring: a probability of detection case study
AC Cobb, JE Michaels, TE Michaels
AIP Conference Proceedings 1096 (1), 1800-1807, 2009
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset
I Kiskin, AD Cobb, L Wang, S Roberts
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Introducing an explicit symplectic integration scheme for Riemannian manifold Hamiltonian Monte Carlo
AD Cobb, AG Baydin, A Markham, SJ Roberts
arXiv preprint arXiv:1910.06243, 2019
New magnetostrictive transducer designs for emerging application areas of NDE
S Vinogradov, A Cobb, J Fisher
Materials 11 (5), 755, 2018
Nonlinear ultrasonic measurements with EMATs for detecting pre-cracking fatigue damage
A Cobb, M Capps, C Duffer, J Feiger, K Robinson, B Hollingshaus
AIP Conference Proceedings 1430 (1), 299-306, 2012
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity
W Fruehwirt, AD Cobb, M Mairhofer, L Weydemann, H Garn, R Schmidt, ...
arXiv preprint arXiv:1812.04994, 2018
Flaw depth sizing using guided waves
AC Cobb, JL Fisher
AIP Conference Proceedings 1706 (1), 030013, 2016
Simultaneous ultrasonic monitoring of crack growth and dynamic loads during a full scale fatigue test of an aircraft wing
TE Michaels, JE Michaels, AC Cobb
AIP Conference Proceedings 1096 (1), 1458-1465, 2009
The practicalities of scaling Bayesian neural networks to real-world applications
AD Cobb
University of Oxford, 2020
Bayesian deep learning for exoplanet atmospheric retrieval
F Soboczenski, MD Himes, MD O'Beirne, S Zorzan, AG Baydin, AD Cobb, ...
arXiv preprint arXiv:1811.03390, 2018
Development of a novel omnidirectional magnetostrictive transducer for plate applications
S Vinogradov, A Cobb, J Bartlett, Y Udagawa
AIP Conference Proceedings 1949 (1), 090002, 2018
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