Search Results for author: Andrew Howes

Found 7 papers, 2 papers with code

Amortised Design Optimization for Item Response Theory

no code implementations19 Jul 2023 Antti Keurulainen, Isak Westerlund, Oskar Keurulainen, Andrew Howes

In education, IRT is used to infer student abilities and characteristics of test items from student responses.

Experimental Design

Amortised Experimental Design and Parameter Estimation for User Models of Pointing

no code implementations19 Jul 2023 Antti Keurulainen, Isak Westerlund, Oskar Keurulainen, Andrew Howes

User models play an important role in interaction design, supporting automation of interaction design choices.

Experimental Design

Online simulator-based experimental design for cognitive model selection

1 code implementation3 Mar 2023 Alexander Aushev, Aini Putkonen, Gregoire Clarte, Suyog Chandramouli, Luigi Acerbi, Samuel Kaski, Andrew Howes

In this paper, we propose BOSMOS: an approach to experimental design that can select between computational models without tractable likelihoods.

Experimental Design Model Selection

Likelihood-Free Inference in State-Space Models with Unknown Dynamics

2 code implementations NeurIPS Workshop Deep_Invers 2021 Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski

Likelihood-free inference (LFI) has been successfully applied to state-space models, where the likelihood of observations is not available but synthetic observations generated by a black-box simulator can be used for inference instead.

Implications of Human Irrationality for Reinforcement Learning

no code implementations7 Jun 2020 Haiyang Chen, Hyung Jin Chang, Andrew Howes

Recent work in the behavioural sciences has begun to overturn the long-held belief that human decision making is irrational, suboptimal and subject to biases.

BIG-bench Machine Learning Decision Making +2

Inferring Cognitive Models from Data using Approximate Bayesian Computation

no code implementations2 Dec 2016 Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta

An important problem for HCI researchers is to estimate the parameter values of a cognitive model from behavioral data.

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