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06/13/2023
DreamDecompiler: Improved Bayesian Program Learning by Decompiling Amortised Knowledge
Solving program induction problems requires searching through an enormou...
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06/07/2023
Bayesian Optimisation Against Climate Change: Applications and Benchmarks
Bayesian optimisation is a powerful method for optimising black-box func...
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05/12/2023
Designing Optimal Behavioral Experiments Using Machine Learning
Computational models are powerful tools for understanding human cognitio...
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05/12/2023
Selective imitation on the basis of reward function similarity
Imitation is a key component of human social behavior, and is widely use...
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02/21/2023
Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making
We present a novel framework to generate causal explanations for the dec...
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06/20/2022
Actively learning to learn causal relationships
How do people actively learn to learn? That is, how and when do people c...
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06/17/2022
A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning
Inscrutable AI systems are difficult to trust, especially if they operat...
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05/30/2022
Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
Unlike literal expressions, idioms' meanings do not directly follow from...
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02/15/2022
Bayesian Optimisation for Active Monitoring of Air Pollution
Air pollution is one of the leading causes of mortality globally, result...
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11/20/2021
Building Object-based Causal Programs for Human-like Generalization
We present a novel task that measures how people generalize objects' cau...
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10/29/2021
Bayesian Optimal Experimental Design for Simulator Models of Cognition
Bayesian optimal experimental design (BOED) is a methodology to identify...
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12/19/2020
Optimising Placement of Pollution Sensors in Windy Environments
Air pollution is one of the most important causes of mortality in the wo...
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10/26/2015
