Arinbjörn Kolbeinsson

According to our database, Arinbjörn Kolbeinsson authored at least 15 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Generative models for wearables data.

Arinbjörn Kolbeinsson, Luca Foschini

CoRR, 2023

STASIS: Reinforcement Learning Simulators for Human-Centric Real-World Environments.

Georgios Efstathiadis, Patrick Emedom-Nnamdi, Arinbjörn Kolbeinsson, Jukka-Pekka Onnela, Junwei Lu

Proceedings of the Trustworthy Machine Learning for Healthcare, 2023

Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections.

Mike A. Merrill, Esteban Safranchik, Arinbjörn Kolbeinsson, Piyusha Gade, Ernesto Ramirez, Ludwig Schmidt, Luca Foshchini, Tim Althoff

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

Galactic Air Improves Ancillary Revenues with Dynamic Personalized Pricing.

Arinbjörn Kolbeinsson, Naman Shukla, Akhil Gupta, Lavanya Marla, Kartik Yellepeddi

INFORMS J. Appl. Anal., 2022

Deep Contrastive Anomaly Detection for Airline Ancillaries Prediction.

Pu Yang, Arinbjörn Kolbeinsson, Naman Shukla, Javier A. Barria

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

Tensor Dropout for Robust Learning.

Arinbjörn Kolbeinsson, Jean Kossaifi, Yannis Panagakis, Adrian Bulat, Animashree Anandkumar, Ioanna Tzoulaki, Paul M. Matthews

IEEE J. Sel. Top. Signal Process., 2021

Self-supervision of wearable sensors time-series data for influenza detection.

Arinbjörn Kolbeinsson, Piyusha Gade, Raghu Kainkaryam, Filip Jankovic, Luca Foschini

CoRR, 2021

PenDer: Incorporating Shape Constraints via Penalized Derivatives.

Akhil Gupta, Lavanya Marla, Ruoyu Sun, Naman Shukla, Arinbjörn Kolbeinsson

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Tensor Regression Networks.

Jean Kossaifi, Zachary C. Lipton, Arinbjörn Kolbeinsson, Aran Khanna, Tommaso Furlanello, Anima Anandkumar

J. Mach. Learn. Res., 2020

GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability.

Daniel Lengyel, Janith C. Petangoda, Isak Falk, Kate Highnam, Michalis Lazarou, Arinbjörn Kolbeinsson, Marc Peter Deisenroth, Nicholas R. Jennings

CoRR, 2020

Patch-Based Brain Age Estimation from MR Images.

Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson, Alexander Hammers, Daniel Rueckert

Proceedings of the Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, 2020

2019

Biologically inspired architectures for sample-efficient deep reinforcement learning.

Pierre H. Richemond, Arinbjörn Kolbeinsson, Yike Guo

CoRR, 2019

Adaptive Model Selection Framework: An Application to Airline Pricing.

Naman Shukla, Arinbjörn Kolbeinsson, Lavanya Marla, Kartik Yellepeddi

CoRR, 2019

Stochastically Rank-Regularized Tensor Regression Networks.

Arinbjörn Kolbeinsson, Jean Kossaifi, Yannis Panagakis, Anima Anandkumar, Ioanna Tzoulaki, Paul M. Matthews

CoRR, 2019

Dynamic Pricing for Airline Ancillaries with Customer Context.

Naman Shukla, Arinbjörn Kolbeinsson, Ken Otwell, Lavanya Marla, Kartik Yellepeddi

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019