The Effect of Training Data Quantity on Monte Carlo Dropout Uncertainty Quantification in Deep Learning.
Harrison CusackAlina BialkowskiPublished in: IJCNN (2023)
Keyphrases
- monte carlo
- deep learning
- training data
- unsupervised learning
- unsupervised feature learning
- importance sampling
- markov chain
- monte carlo simulation
- machine learning
- monte carlo tree search
- mental models
- learning algorithm
- data sets
- markovian decision
- prior knowledge
- decision trees
- supervised learning
- variance reduction
- training set
- adaptive sampling
- computer vision
- labeled data
- matrix inversion
- training samples
- particle filter
- active learning