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that explicitly account for drift and open-set contamination. O2: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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. Among the approaches used will be the Bayesian information-theoretic Minimum Message Length (MML) principle (Wallace and Boulton, 1968; Wallace and Dowe, 1999a; Wallace, 2005) References: Wallace, C.S
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-Enhanced Learning Analytics for Adaptive Early Intervention in Higher Education Bayesian Uncertainty Estimation for Robust Single- and Multi-View Learning in CV and NLP Robust Active Learning Under
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Education Bayesian Uncertainty Estimation for Robust Single- and Multi-View Learning in CV and NLP Robust Active Learning Under Distribution Drift Data-Efficient Deep Learning for De Novo Molecular Design
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of Unknown Functions Quantum-Enhanced Learning Analytics for Adaptive Early Intervention in Higher Education Bayesian Uncertainty Estimation for Robust Single- and Multi-View Learning in CV and NLP Robust
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Masters project Supervisors Login Recently added Blackbox Optimization of Unknown Functions Quantum-Enhanced Learning Analytics for Adaptive Early Intervention in Higher Education Bayesian Uncertainty
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used will the information-theoretic Bayesian minimum message length (MML) principle. Student cohort PhD, possibly Master’s (Minor Thesis) or Honours URLs/references Chen, Li and Gao, Jiti and Vahid
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. Butler, C. Goncu, and L. Holloway. Tactile presentation of network data: Text, matrix or diagram? In CHI2020, pages 1–12, 2020. I. Zukerman et al.˙Exploratory Interaction with a Bayesian Argumentation
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, Joshua W. and D.L. Dowe (2005). ``Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages'', Chapter 11 (pp265-294) in P. Gru:nwald, I. J. Myung and M. A. Pitt (eds.), Advances in