Articles with public access mandates - Scott Cheng-Hsin YangLearn more
Available somewhere: 21
Theoretical perspectives on active sensing
SCH Yang, DM Wolpert, M Lengyel
Current opinion in behavioral sciences 11, 100-108, 2016
Mandates: Wellcome Trust, Human Frontier Science Program
Active sensing in the categorization of visual patterns
SCH Yang, M Lengyel, DM Wolpert
Elife 5, e12215, 2016
Mandates: Wellcome Trust, Human Frontier Science Program
Replication timing is regulated by the number of MCMs loaded at origins
SP Das, T Borrman, VWT Liu, SCH Yang, J Bechhoefer, N Rhind
Genome Research 25 (12), 1886-1892, 2015
Mandates: US National Institutes of Health, Natural Sciences and Engineering Research …
Reconciling stochastic origin firing with defined replication timing
N Rhind, SCH Yang, J Bechhoefer
Chromosome Research 18, 35-43, 2010
Mandates: US National Institutes of Health
The theoretical and methodological opportunities afforded by guided play with young children
Y Yu, P Shafto, E Bonawitz, SCH Yang, RM Golinkoff, KH Corriveau, ...
Frontiers in psychology 9, 1152, 2018
Mandates: US National Science Foundation
Mitigating belief projection in explainable artificial intelligence via Bayesian teaching
SCH Yang, WK Vong, RB Sojitra, T Folke, P Shafto
Scientific reports 11 (1), 9863, 2021
Mandates: US National Science Foundation, US Department of Defense
Explainable artificial intelligence via bayesian teaching
SCH Yang, P Shafto
NIPS 2017 workshop on teaching machines, robots, and humans 2, 2017
Mandates: US Department of Defense
Explainable AI for medical imaging: explaining pneumothorax diagnoses with Bayesian teaching
T Folke, SCH Yang, S Anderson, P Shafto
Artificial Intelligence and Machine Learning for Multi-Domain Operations …, 2021
Mandates: US National Science Foundation, US Department of Defense
Optimal cooperative inference
SCH Yang, Y Yu, P Wang, WK Vong, P Shafto
International Conference on Artificial Intelligence and Statistics, 376-385, 2018
Mandates: US National Science Foundation, US Department of Defense
A psychological theory of explainability
SCH Yang, NET Folke, P Shafto
International Conference on Machine Learning, 25007-25021, 2022
Mandates: US National Science Foundation, US Department of Defense
Interpretable deep Gaussian processes with moments
CK Lu, SCH Yang, X Hao, P Shafto
International Conference on Artificial Intelligence and Statistics, 613-623, 2020
Mandates: US Department of Defense
A unifying computational framework for teaching and active learning
SCH Yang, WK Vong, Y Yu, P Shafto
Topics in cognitive science 11 (2), 316-337, 2019
Mandates: US National Science Foundation, US Department of Defense
Abstraction, validation, and generalization for explainable artificial intelligence
SCH Yang, T Folke, P Shafto
Applied AI Letters 2 (4), e37, 2021
Mandates: US National Science Foundation, US Department of Defense
Teaching versus active learning: A computational analysis of conditions that affect learning
SCH Yang, P Shafto
Proceedings of the Annual Meeting of the Cognitive Science Society 39, 2017
Mandates: US National Science Foundation
Bayesian Teaching of Image Categories.
WK Vong, RB Sojitra, A Reyes, SCH Yang, P Shafto
CogSci, 2018
Mandates: US Department of Defense
Evaluating perceptual and semantic interpretability of saliency methods: A case study of melanoma
PS Harshit Bokadia, Scott Cheng-Hsin Yang, Zhaobin Li, Tomas Folke
Applied AI Letters 3 (3), e77, 2022
Mandates: US National Science Foundation, US Department of Defense
Unifying recommendation and active learning for information filtering and recommender systems
SCH Yang, C Rank, J Whritner, O Nasraoui, P Shafto
PsyArXiv, 2020
Mandates: US National Science Foundation
Modeling second language preposition learning
L Barak, SCH Yang, C Rank, P Shafto
Proc. of CogSci, 3151-3157, 2020
Mandates: US National Science Foundation, US Department of Defense, US National …
Standing-wave-decomposition Gaussian process
CK Lu, SCH Yang, P Shafto
Physical Review E 98 (3), 032303, 2018
Mandates: US Department of Defense
Unifying recommendation and active learning for human-algorithm interactions.
SCH Yang, JA Whritner, O Nasraoui, P Shafto
CogSci, 2017
Mandates: US National Science Foundation
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