From Displacements to Distributions: A Machine-Learning Enabled Framework for Quantifying Uncertainties in Parameters of Computational Models.
Taylor RoperHarri HakulaTroy ButlerPublished in: CoRR (2024)
Keyphrases
- computational models
- computational model
- machine learning
- cognitive modelling
- natural language processing
- probabilistic model
- artificial intelligence
- optical flow
- computer vision
- human computer interaction
- language acquisition
- maximum likelihood
- parameter estimation
- bayesian framework
- probability density function
- learning algorithm
- normal distribution
- measured data
- data mining