Frank Soboczenski

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Adam D CobbSRI InternationalZweryfikowany adres z sri.com
Atılım Güneş BaydinUniversity of OxfordZweryfikowany adres z robots.ox.ac.uk
Shawn Domagal-GoldmanResearch Space Scientist at NASA Goddard Space Flight CenterZweryfikowany adres z nasa.gov
Giada ArneyNASA Goddard Space Flight CenterZweryfikowany adres z nasa.gov
Byron WallaceAssociate Professor, Northeastern UniversityZweryfikowany adres z ccs.neu.edu
Iain MarshallKing's College LondonZweryfikowany adres z kcl.ac.uk
Yarin GalAssociate Professor, University of OxfordZweryfikowany adres z cs.ox.ac.uk
Iain BateReal-Time Systems Group (RTSRG), University of YorkZweryfikowany adres z york.ac.uk
David GriffinResearch Associate, RTSRG, University of YorkZweryfikowany adres z york.ac.uk
Paul CairnsProfessor of Human-Computer Interaction, University of YorkZweryfikowany adres z york.ac.uk
Rob DavisReader, Real-Time and Distributed Systems Research Group, University of York, UK.Zweryfikowany adres z york.ac.uk
John Kalantari, Ph.D.Assistant Professor, Director of AI/MLZweryfikowany adres z mayo.edu
Kia KhezeliCornell UniversityZweryfikowany adres z cornell.edu
Nicholas ChiaData Science and LearningZweryfikowany adres z anl.gov
James ThomasProfessor of Social Research & Policy, EPPI-Centre, UCL Social Research Institute, UCLZweryfikowany adres z ioe.ac.uk
Anna Noel-StorrCochrane Crowd Lead and Information Specialist, University of OxfordZweryfikowany adres z rdm.ox.ac.uk
Benjamin E NyeColorado CollegeZweryfikowany adres z coloradocollege.edu
Thomas TrikalinosHealth Services, Policy & PracticeZweryfikowany adres z brown.edu
Samuel BuddImperial College London, Kings College LondonZweryfikowany adres z imperial.ac.uk
Adrienne HoarfrostUniversity of GeorgiaZweryfikowany adres z uga.edu

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Frank Soboczenski

Assistant Professor, University of York & Affiliate King's College London

Zweryfikowany adres z york.ac.uk - Strona główna

Machine Learning Human-Computer Interaction Natural Language Processing Data Science Space Science


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
An ensemble of bayesian neural networks for exoplanetary atmospheric retrieval AD Cobb, MD Himes, F Soboczenski, S Zorzan, MD O’Beirne, AG Baydin, ... The astronomical journal 158 (1), 33, 2019	67	2019
Generating (factual?) narrative summaries of rcts: Experiments with neural multi-document summarization BC Wallace, S Saha, F Soboczenski, IJ Marshall AMIA Summits on Translational Science Proceedings 2021, 605, 2021	55	2021
Trialstreamer: A living, automatically updated database of clinical trial reports IJ Marshall, B Nye, J Kuiper, A Noel-Storr, R Marshall, R Maclean, ... Journal of the American Medical Informatics Association 27 (12), 1903-1912, 2020	54	2020
Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study F Soboczenski, TA Trikalinos, J Kuiper, RG Bias, BC Wallace, IJ Marshall BMC Medical Informatics and Decision Making 19, 1-12, 2019	43	2019
Accurate machine-learning atmospheric retrieval via a neural-network surrogate model for radiative transfer MD Himes, J Harrington, AD Cobb, AG Baydin, F Soboczenski, ... The Planetary Science Journal 3 (4), 91, 2022	28	2022
Forecast-based interference: Modelling multicore interference from observable factors D Griffin, B Lesage, I Bate, F Soboczenski, RI Davis Proceedings of the 25th International Conference on Real-Time Networks and …, 2017	23	2017
A framework for the evaluation of measurement-based timing analyses B Lesage, D Griffin, F Soboczenski, I Bate, RI Davis Proceedings of the 23rd international conference on real time and networks …, 2015	22	2015
State of the evidence: a survey of global disparities in clinical trials IJ Marshall, V L'Esperance, R Marshall, J Thomas, A Noel-Storr, ... BMJ global health 6 (1), e004145, 2021	18	2021
Study of the reliability of statistical timing analysis for real-time systems D Maxim, F Soboczenski, I Bate, E Tovar Proceedings of the 23rd international conference on real time and networks …, 2015	15	2015
On invariance penalties for risk minimization K Khezeli, A Blaas, F Soboczenski, N Chia, J Kalantari arXiv preprint arXiv:2106.09777, 2021	14	2021
Prototyping CRISP: a Causal Relation and Inference Search Platform applied to colorectal cancer data S Budd, A Blaas, A Hoarfrost, K Khezeli, K D'Silva, F Soboczenski, ... 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech …, 2021	13	2021
Biomonitoring and precision health in deep space supported by artificial intelligence RT Scott, LM Sanders, EL Antonsen, JJA Hastings, S Park, G Mackintosh, ... Nature Machine Intelligence 5 (3), 196-207, 2023	11	2023
Increasing accuracy by decreasing presentation quality in transcription tasks F Soboczenski, P Cairns, AL Cox Human-Computer Interaction–INTERACT 2013: 14th IFIP TC 13 International …, 2013	11	2013
Bayesian deep learning for exoplanet atmospheric retrieval F Soboczenski, MD Himes, MD O'Beirne, S Zorzan, AG Baydin, AD Cobb, ... arXiv preprint arXiv:1811.03390, 2018	10	2018
Biological research and self-driving labs in deep space supported by artificial intelligence LM Sanders, RT Scott, JH Yang, AA Qutub, H Garcia Martin, DC Berrios, ... Nature Machine Intelligence 5 (3), 208-219, 2023	9	2023
In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving IJ Marshall, TA Trikalinos, F Soboczenski, HS Yun, G Kell, R Marshall, ... Journal of Clinical Epidemiology 153, 26-33, 2023	8	2023
Visualizing magnitude: Graphical number representations help users detect large number entry errors J Borghouts, F Soboczenski, P Cairns, DP Brumby Proceedings of the Human Factors and Ergonomics Society Annual Meeting 59 (1 …, 2015	8	2015
Evaluating mixed criticality scheduling algorithms with realistic workloads D Griffin, I Bate, B Lesage, F Soboczenski Proceedings of Workshop on Mixed Criticality (WMC), 2015	8	2015
Beyond low earth orbit: biomonitoring, artificial intelligence, and precision space health RT Scott, EL Antonsen, LM Sanders, JJA Hastings, S Park, G Mackintosh, ... arXiv preprint arXiv:2112.12554, 2021	5	2021
Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different? AV Dalca, MBA McDermott, E Alsentzer, SG Finlayson, M Oberst, F Falck, ... Machine Learning for Health Workshop, 1-9, 2020	4	2020

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