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Sabina J. Sloman
Sabina J. Sloman
Department of Computer Science, University of Manchester
Подтвержден адрес электронной почты в домене manchester.ac.uk
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Процитировано
Процитировано
Год
Beyond collective intelligence: Collective adaptation
M Galesic, D Barkoczi, AM Berdahl, D Biro, G Carbone, I Giannoccaro, ...
Journal of the Royal Society Interface 20 (200), 20220736, 2023
282023
Life satisfaction among Aboriginals in the Canadian Prairies: Evidence from the Equality, Security and Community survey
C Barrington-Leigh, S Sloman
The International Indigenous Policy Journal 7 (2), 2016
112016
Interpreting model comparison requires understanding model-stimulus relationships
SB Broomell, SJ Sloman, LM Blaha, J Chelen
Computational Brain & Behavior 2, 233-238, 2019
102019
Can we detect conditioned variation in political speech? Two kinds of discussion and types of conversation
SJ Sloman, DM Oppenheimer, S DeDeo
Plos one 16 (2), e0246689, 2021
92021
Think of the consequences: A decade of discourse about same-sex marriage
B Hemmatian, SJ Sloman, U Cohen Priva, SA Sloman
Behavior Research Methods 51, 1565-1585, 2019
92019
Characterizing the robustness of Bayesian adaptive experimental designs to active learning bias
SJ Sloman, DM Oppenheimer, SB Broomell, CR Shalizi
arXiv preprint arXiv:2205.13698, 2022
62022
A Social Interpolation Model of Group Problem‐Solving
SJ Sloman, RL Goldstone, C Gonzalez
Cognitive Science 45 (12), e13066, 2021
62021
Knowing what to know: Implications of the choice of prior distribution on the behavior of adaptive design optimization
SJ Sloman, D Cavagnaro, SB Broomell
arXiv preprint arXiv:2303.12683, 2023
42023
Complex exploration dynamics from simple heuristics in a collective learning environment.
S Sloman, RL Goldstone, C Gonzalez
CogSci, 2818-2824, 2019
32019
You Take the High Road, and I’ll Take the Low Road: Evaluating the Topographical Consistency of Cognitive Models
SJ Sloman, D Oppenheimer
Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society, 2020
22020
Diagnosing pervasive issues with parameter estimation.
S Sloman, S Broomell, T Kusuma
CogSci, 2020
22020
Explore your experimental designs and theories before you exploit them!
M Dubova, SJ Sloman, B Andrew, MR Nassar, S Musslick
Behavioral and Brain Sciences 47, e40, 2024
12024
The Fundamental Dilemma of Bayesian Active Meta-learning
SJ Sloman, A Bharti, S Kaski
arXiv preprint arXiv:2310.14968, 2023
12023
A Comparison of Methods for Adaptive Experimentation
S Horn, SJ Sloman
arXiv preprint arXiv:2207.00683, 2022
12022
Learning relevant contextual variables within Bayesian optimization
J Martinelli, A Bharti, A Tiihonen, L Filstroff, ST John, SJ Sloman, P Rinke, ...
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in …, 2023
2023
Bayesian Active Meta-Learning under Prior Misspecification
SJ Sloman, A Bharti, S Kaski
2023
Cost-aware learning of relevant contextual variables within Bayesian optimization
J Martinelli, A Bharti, ST John, A Tiihonen, S Sloman, L Filstroff, S Kaski
arXiv preprint arXiv:2305.14120, 2023
2023
Excess Capacity Learning
M Dubova, SJ Sloman
Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023
2023
57: INTENSIVIST PHYSICIANS’KNOWLEDGE AND ATTITUDES ABOUT BAYESIAN ADAPTIVE CLINICAL TRIALS
B Malley, J Levin, A Althouse, S Sloman, J Kahn, D Huang
Critical Care Medicine 51 (1), 29, 2023
2023
Towards robust Bayesian adaptive design methods for the study of human behavior
SJ Sloman
Carnegie Mellon University, 2022
2022
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Статьи 1–20