Publications

View By Topic:
All Topics
F Foundations
P Perception
E Education
CI Causal Induction
CD Cognitive Development
PR Probabilistic Reasoning
RPM Rational Process Models
S&C Similarity and Categorization
SML Statistical Models of Language
NBM Nonparametric Bayesian Models
CEIL Cultural Evolution and Iterated Learning
DMRL Decision Making and Reinforcement Learning

(Click on an author's name to view all papers by that author.)


Filter publications

By Levine, S.
NBM
DMRL
Chang, M., Dayan, A. L., Meier, F., Griffiths, T. L., Levine, S., & Zhang, A. (2023). Neural Constraint Satisfaction: Hierarchical abstraction for combinatorial generalization in object rearrangement. Proceedings of the 11th International Conference on Learning Representations. (pdf)
S&C
Chang, M., Griffiths, T. L., & Levine, S. (2022). Object representations as fixed points: Training iterative refinement algorithms with implicit differentiation. Advances in Neural Information Processing Systems, 36. (pdf)
DMRL
Chang, M., Kaushik, S., Weinberg, S. M., Griffiths, T., & Levine, S. (2020). Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. Proceedings of the International Conference on Machine Learning. (pdf)
RPM
DMRL
Chang, M. B., Gupta, A., Levine, S., & Griffiths, T. L. (2019). Automatically composing representation transformations as a means for generalization. Proceedings of the 7th International Conference on Learning Representations (ICLR) 2019. (pdf)
PR
Grant, E., Finn, C., Levine, S., Darrell, T., & Griffiths, T. L. (2018). Recasting gradient-based meta-learning as hierarchical Bayes. In Proceedings of the 6th International Conference on Learning Representations (ICLR). (pdf)

© 2024 Computational Cognitive Science Lab  |  Department of Psychology  |  Princeton University