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By Dasgupta, I.S&C Dasgupta, I. , Grant, E. , & Griffiths, T. L. (2022). Distinguishing rule- and exemplar-based generalization in learning systems. Proceedings of the International Conference on Machine Learning. (pdf)
RPM S&C Dasgupta, I. , & Griffiths, T. L. (2022). Clustering and the efficient use of cognitive resources. Journal of Mathematical Psychology, 109, 102675. (pdf)
SML DMRL Kumar, S. , Correa, C. G. , Dasgupta, I. , Marjieh, R. , Hu, M. Y. , Hawkins, R.D. , Daw, N. D. , Cohen, J. D. , Narasimhan, K. R. , & Griffiths, T. L. (2022). Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines. Advances in Neural Information Processing Systems, 36. (preprint link)
SML DMRL Kumar, S. , Dasgupta, I. , Hu, M. Y. , Marjieh, R. , Hawkins, R. D. , Daw, N. , Cohen, J. , Narasimhan, K. R. , & Griffiths, T. L. (2022). Using Natural Language to Guide Meta-Learning Agents towards Human-like Inductive Biases. BACL 1st Workshop on Learning with Natural Language Supervision. (pdf)
DMRL Kumar, S. , Dasgupta, I. , Marjieh, R. , Daw, N. D. , Cohen, J. D. , & Griffiths, T. L. (2022). Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. (preprint link)
DMRL Kumar, S. , Dasgupta, I. , Cohen, J. D. , Daw, N. D. , & Griffiths, T. L. (2021). Meta-learning of structured task distributions in humans and machines. Proceedings of the 9th International Conference on Learning Representations (ICLR) . (pdf)
P Langlois, T. A. , Zhao, H. C. , Grant, E. , Dasgupta, I. , Griffiths, T. L. , & Jacoby, N. (2021). Passive attention in artificial neural networks predicts human visual selectivity. Advances in Neural Information Processing Systems, 34. (pdf)
P Tuli, S. , Dasgupta, I. , Grant, E. , & Griffiths, T. L. (2021). Are Convolutional Neural Networks or Transformers more like human vision?. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. (link)