Erlend Aune

Forsker II - Institutt for datavitenskap og analyse


Lee, Daesoo; Aune, Erlend, Langet, Nadege & Eidsvik, Jo (2022)

Ensemble and Self-supervised Learning for Improved Classification of Seismic Signals from the Åknes Rockslope

Mathematical Geosciences Doi: 10.1007/s11004-022-10037-7

A case study with seismic geophone data from the unstable Åknes rock slope in Norway is considered. This rock slope is monitored because there is a risk of severe flooding if the massive-size rock falls into the fjord. The geophone data is highly valuable because it provides 1000 Hz sampling rates data which are streamed to a web resource for real-time analysis. The focus here is on building a classifier for these data to distinguish different types of microseismic events which are in turn indicative of the various processes occurring on the slope. There are 24 time series from eight 3-component geophone data for about 3500 events in total, and each of the event time series has a length of 16 s. For the classification task, novel machine learning methods such as deep convolutional neural networks are leveraged. Ensemble prediction is used to extract information from all time series, and this is seen to give large improvements compared with doing immediate aggregation of the data. Further, self-supervised learning is evaluated to give added value here, in particular for the case with very limited training data.

Vassøy, Bjørnar; Ruocco, Massimiliano, de Souza da Silva, Eliezer & Aune, Erlend (2019)

Time is of the essence: A joint Hierarchical RNN and Point Process model for time and item predictions

Jung, Jason J. (red.). WIMS2019 Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics

Aune, Erlend; Eidsvik, Jo & Ursin, Bjørn (2013)

Three-dimensional non-stationary and non-linear isotropic AVA inversion

Geophysical Journal International, 194(2), s. 787- 803. Doi: 10.1093/gji/ggt127

Aune, Erlend; Eidsvik, Jo & Pokern, Y (2013)

Iterative numerical methods for sampling from high dimensional Gaussian distributions

Statistics and computing, 23(4), s. 501- 521. Doi: 10.1007/s11222-012-9326-8

Saplacan, Diana; Foldnes, Njål, Aune, Erlend, Dahl, Ida, Voigt, Jakob Michael & Goodwin, Morten (2021)

AI & pedagogics

Webinar - Norwegian Consortium of Artificial Intelligence [Internett]

Aune, Erlend & Stenvik, Lars Fredrik (2016)

Mektig imponert over jernviljen

Innherred [Avis]

Akademisk grad
År Akademisk institusjon Grad
2012 NTNU Norwegian university of science and technology PhD