Explicit neural signals reflecting reward uncertainty

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As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

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A search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016-2018 at a centre-of-mass energy of 13 TeV a ...

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In this thesis we present three closed form approximation methods for portfolio valuation and risk management. The first chapter is titled ``Kernel methods for portfolio valuation and risk management'', and is a joint work with Damir Filipovi'c (SFI and ...

Explicit neural signals reflecting reward uncertainty

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Extensions of Peer Prediction Incentive Mechanisms

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Can one hear the shape of a target zone?

Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at √s=13 TeV

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Bayes Security: A Not So Average Metric

Striatal Dopamine Signals and Reward Learning

Cloud Condensation Nuclei (CCN) concentrations measured in the Swiss container during MOSAiC 2019/2020

Closed form approximation methods for portfolio valuation and risk management