To learn more about the topics covered in this chapter, read the following papers:
- Human-level concept learning through probabilistic program induction: https://web.mit.edu/cocosci/Papers/Science-2015-Lake-1332-8.pdf
- A Bayesian approach to unsupervised one-shot learning of object categories: http://vision.stanford.edu/documents/Fei-Fei_ICCV03.pdf
- Discriminative k-shot learning using probabilistic models: https://arxiv.org/pdf/1706.00326.pdf
- Building machines that learn and think like people: http://web.stanford.edu/class/psych209/Readings/LakeEtAlBBS.pdf
- One-shot learning of simple visual concepts: https://cims.nyu.edu/~brenden/LakeEtAl2011CogSci.pdf
- One-shot learning with a hierarchical nonparametric Bayesian model: https://www.cs.cmu.edu/~rsalakhu/papers/MIT-CSAIL-TR-2010-052.pdf
