| Tensor regression networks J Kossaifi, ZC Lipton, A Kolbeinsson, A Khanna, T Furlanello, ... Journal of Machine Learning Research 21 (123), 1-21, 2020 | 174 | 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 | 65* | 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 | 56 | 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 | 53 | 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 | 37* | 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 | 20 | 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 | 16 | 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 | 13* | 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 | 8 | 2020 |
| Adaptive model selection framework: An application to airline pricing N Shukla, A Kolbeinsson, L Marla, K Yellepeddi arXiv preprint arXiv:1905.08874, 2019 | 8 | 2019 |
| 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 | 5 | 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 | 5 | 2023 |
| 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 | 5 | 2021 |
| 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 | 4 | 2020 |
| Biologically inspired architectures for sample-efficient deep reinforcement learning PH Richemond, A Kolbeinsson, Y Guo arXiv preprint arXiv:1911.11285, 2019 | 3 | 2019 |
| 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 | 2 | 2023 |
| Generative models for wearables data A Kolbeinsson, L Foschini Workshop on Deep Generative Models for Health at NeurIPS, 2023 | 1 | 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 | 1 | 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 | | 2024 |
| Kvikir samningsstaðlar A Kolbeinsson Háskóli Íslands, 2024 | | 2024 |
Naman ShuklaFLYR Labs在 illinois.edu 的电子邮件经过验证
