About
Hammer has a master in industrial mathematics from 2003 and a PhD in computational statistics from 2008. His main research interests are within improving reliability and transparency of machine learning, reinforcement learning and deep learning models by developing methods within model interpretation, uncertainty quantification, robust statistics and causal inference.
Fields of study
Academic disciplines
Subject areas
Bayesian statistics Regression Artificial intelligence Machine learning Applied statistics Stochastic simulation Big Data
Countries
Research groups
Research projects
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Artificial intelligence - a novel tool in assisted reproduction technology
The project aims to improve the methods for selecting sperm and embryos and increase the chance of pregnancy and live-born children.
Publications and research
Scientific publications
Boeker, Matthias; Jakobsen, Petter; Riegler, Michael; Stabell, Lena Antonsen; Fasmer, Ole Bernt; Halvorsen, Pål; Hammer, Hugo Lewi (2023). Affect Recognition in Muscular Response Signals. IEEE Access . Vol. 11.
Storås, Andrea; Riegler, Michael Alexander; Haugen, Trine B.; Thambawita, Vajira L B; Hicks, Steven Alexander; Hammer, Hugo Lewi; Kakulavarapu, Radhika; Halvorsen, Pål; Stensen, Mette Haug (2023). Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure. Zouganeli, Evi; Yazidi, Anis; Mello, Gustavo Borges Moreno E; Lind, Pedro (Ed.). Nordic Artificial Intelligence Research and Development: 4th Symposium of the Norwegian AI Society, NAIS 2022, Oslo, Norway, May 31-June 1, 2022, Revised Selected Papers. konferanseartikkel. Springer Nature.
Storås, Andrea; Prabhu, Robindra; Hammer, Hugo Lewi; Strumke, Inga
(2022).
Bias og kvantitativ analyse innen velferd: opphav til skjevheter og relasjon til utfallsrettferdighet.
24 p.
Tidsskrift for velferdsforskning
.
Vol. 25.
https://hdl.handle.net/11250/3054535
Boeker, Matthias; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; Jakobsen, Petter
(2022).
Prediction of schizophrenia from activity data using hidden Markov model parameters.
Neural Computing & Applications
.
https://hdl.handle.net/10037/28614
Thambawita, Vajira L B; Salehi, Pegah; Sheshkal, Sajad Amouei; Hicks, Steven; Hammer, Hugo Lewi; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (2022). SinGAN-Seg: Synthetic training data generation for medical image segmentation. PLOS ONE . Vol. 17.
Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard
(2022).
Efficient quantile tracking using an oracle.
12 p.
Applied intelligence (Boston)
.
https://hdl.handle.net/10037/26509
Eide, Siri Sofie; Riegler, Michael; Hammer, Hugo Lewi; Bremnes, John Bjørnar
(2022).
Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources.
Sensors
.
Vol. 22.
https://hdl.handle.net/10037/26522
Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard
(2022).
Estimating Tukey depth using incremental quantile estimators.
11 p.
Pattern Recognition
.
Vol. 122.
https://hdl.handle.net/11250/2983184
Storås, Andrea; Strumke, Inga; Riegler, Michael Alexander; Grauslund, Jakob; Hammer, Hugo Lewi; Yazidi, Anis; Halvorsen, Pål; Gundersen, Kjell Gunnar; Utheim, Tor Paaske; Jackson, Catherine Joan (2021). Artificial intelligence in dry eye disease. The ocular surface . Vol. 23.
Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (2021). Joint tracking of multiple quantiles through conditional quantiles. Information Sciences . Vol. 563.
