Parameter-efficient fine-tuning of PhaseNO with 200 microseismic examples yields up to 30% better phase picking performance than the original model on independent test datasets.
In: International Confer- ence on Machine Learning, pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.geo-ph 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Parameter-Efficient Transfer Learning for Microseismic Phase Picking Using a Neural Operator
Parameter-efficient fine-tuning of PhaseNO with 200 microseismic examples yields up to 30% better phase picking performance than the original model on independent test datasets.