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Using Machine Learning to Discern Eruption in Noisy Environments: A Case
  Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico

Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico

1 October 2018
Baichuan Yuan
Yen Joe Tan
M. Mudunuru
O. Marcillo
A. Delorey
P. Roberts
Jeremy D. Webster
C. Gammans
S. Karra
G. Guthrie
Paul Johnson
ArXiv (abs)PDFHTML

Papers citing "Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico"

3 / 3 papers shown
Title
Perspectives on AI Architectures and Co-design for Earth System
  Predictability
Perspectives on AI Architectures and Co-design for Earth System Predictability
M. Mudunuru
James A. Ang
M. Halappanavar
Simon D. Hammond
Maya Gokhale
...
Tushar Krishna
S. Sreepathi
Matthew R. Norman
Ivy Bo Peng
Philip W. Jones
36
1
0
07 Apr 2023
A Comparative Study of Machine Learning Models for Predicting the State
  of Reactive Mixing
A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing
B. Ahmmed
M. Mudunuru
S. Karra
S. James
V. Vesselinov
46
15
0
24 Feb 2020
Physics-Informed Machine Learning Models for Predicting the Progress of
  Reactive-Mixing
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing
M. Mudunuru
S. Karra
47
11
0
28 Aug 2019
1