Arinbjörn Kolbeinsson
Arinbjörn Kolbeinsson
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Cited by
Cited by
Tensor regression networks
J Kossaifi, ZC Lipton, A Kolbeinsson, A Khanna, T Furlanello, ...
Journal of Machine Learning Research 21 (123), 1-21, 2020
Pender: Incorporating shape constraints via penalized derivatives
A Gupta, L Marla, R Sun, N Shukla, A Kolbeinsson
Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11536 …, 2021
Accelerated MRI-predicted brain ageing and its associations with cardiometabolic and brain disorders
A Kolbeinsson, S Filippi, Y Panagakis, PM Matthews, P Elliott, A Dehghan, ...
Scientific Reports 10 (1), 19940, 2020
Dynamic pricing for airline ancillaries with customer context
N Shukla, A Kolbeinsson, K Otwell, L Marla, K Yellepeddi
Proceedings of the 25th ACM SIGKDD International Conference on knowledge …, 2019
Tensor dropout for robust learning
A Kolbeinsson, J Kossaifi, Y Panagakis, A Bulat, A Anandkumar, ...
IEEE Journal of Selected Topics in Signal Processing 15 (3), 630-640, 2021
Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy
J Lightley, F Görlitz, S Kumar, R Kalita, A Kolbeinsson, E Garcia, ...
Journal of Microscopy 288 (2), 130-141, 2022
Patch-based brain age estimation from MR images
KM Bintsi, V Baltatzis, A Kolbeinsson, A Hammers, D Rueckert
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro …, 2020
Galactic air improves ancillary revenues with dynamic personalized pricing
A Kolbeinsson, N Shukla, A Gupta, L Marla, K Yellepeddi
INFORMS Journal on Applied Analytics 52 (3), 233-249, 2022
From average customer to individual traveler: A field experiment in airline ancillary pricing
N Shukla, A Kolbeinsson, L Marla, K Yellepeddi
Available at SSRN 3518854, 2020
Adaptive model selection framework: An application to airline pricing
N Shukla, A Kolbeinsson, L Marla, K Yellepeddi
arXiv preprint arXiv:1905.08874, 2019
Self-supervision of wearable sensors time-series data for influenza detection
A Kolbeinsson, P Gade, R Kainkaryam, F Jankovic, L Foschini
The workshop on Self-Supervised Learning at NeurIPS (2021), 2021
Systems And Methods For Self-Supervised Learning Based On Naturally-Occurring Patterns Of Missing Data
L Foschini, F Jankovic, RM Kainkaryam, JIO Mendez, A Kolbeinsson
US Patent App. 18/156,010, 2023
Homekit2020: A benchmark for time series classification on a large mobile sensing dataset with laboratory tested ground truth of influenza infections
MA Merrill, E Safranchik, A Kolbeinsson, P Gade, E Ramirez, L Schmidt, ...
Conference on Health, Inference, and Learning, 207-228, 2023
Genni: Visualising the geometry of equivalences for neural network identifiability
D Lengyel, J Petangoda, I Falk, K Highnam, M Lazarou, A Kolbeinsson, ...
arXiv preprint arXiv:2011.07407, 2020
Biologically inspired architectures for sample-efficient deep reinforcement learning
PH Richemond, A Kolbeinsson, Y Guo
arXiv preprint arXiv:1911.11285, 2019
Generative models for wearables data
A Kolbeinsson, L Foschini
Workshop on Deep Generative Models for Health at NeurIPS, 2023
Systems and methods for predicting, detecting, and monitoring of acute illness
L Foschini, E Caddigan, F Jankovic, A Kolbeinsson, B Bradshaw, ...
US Patent App. 18/148,991, 2023
Robust optical autofocus system utilizing neural networks trained for extended range and time-course and automated multiwell plate imaging including single molecule …
J Lightley, F Görlitz, S Kumar, R Kalita, A Kolbeinsson, E Garcia, ...
bioRxiv, 2021.03. 05.431171, 2021
Composable Interventions for Language Models
A Kolbeinsson, K O'Brien, T Huang, S Gao, S Liu, JR Schwarz, A Vaidya, ...
arXiv preprint arXiv:2407.06483, 2024
STASIS: Reinforcement Learning Simulators for Human-Centric Real-World Environments
G Efstathiadis, P Emedom-Nnamdi, A Kolbeinsson, JP Onnela, J Lu
International Workshop on Trustworthy Machine Learning for Healthcare, 85-92, 2023
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