Andrew Kyle Lampinen
Andrew Kyle Lampinen
Research Scientist, DeepMind
Verified email at - Homepage
Cited by
Cited by
An analytic theory of generalization dynamics and transfer learning in deep linear networks
AK Lampinen, S Ganguli
7th International Conference on Learning Representations (ICLR 2019), 2018
Environmental drivers of systematicity and generalization in a situated agent
F Hill, A Lampinen, R Schneider, S Clark, M Botvinick, JL McClelland, ...
arXiv preprint arXiv:1910.00571, 2019
Improving the replicability of psychological science through pedagogy
RXD Hawkins, EN Smith, C Au, JM Arias, R Catapano, E Hermann, M Keil, ...
Advances in Methods and Practices in Psychological Science 1 (1), 7-18, 2018
Integration of new information in memory: new insights from a complementary learning systems perspective
JL McClelland, BL McNaughton, AK Lampinen
Philosophical Transactions of the Royal Society B 375 (1799), 20190637, 2020
Automated curricula through setter-solver interactions
S Racaniere, AK Lampinen, A Santoro, DP Reichert, V Firoiu, TP Lillicrap
8th International Conference on Learning Representations (ICLR 2020), 2019
What shapes feature representations? exploring datasets, architectures, and training
KL Hermann, AK Lampinen
Advances in Neural Information Processing Systems, 2020
One-shot and few-shot learning of word embeddings
AK Lampinen, JL McClelland
arXiv preprint arXiv:1710.10280, 2017
Transforming task representations to perform novel tasks
AK Lampinen, JL McClelland
Proceedings of the National Academy of Sciences 117 (52), 32970-32981, 2020
Different presentations of a mathematical concept can support learning in complementary ways.
AK Lampinen, JL McClelland
Journal of Educational Psychology 110 (5), 664, 2018
Building on prior knowledge without building it in
SS Hansen, AK Lampinen, G Suri, JL McClelland
Behavioral and Brain Sciences 40, 2017
Analogies Emerge from Learning Dyamics in Neural Networks.
AK Lampinen, S Hsu, JL McClelland
CogSci, 2017
Symbolic behaviour in artificial intelligence
A Santoro, A Lampinen, K Mathewson, T Lillicrap, D Raposo
arXiv preprint arXiv:2102.03406, 2021
A Computational Framework for Learning and Transforming Task Representations
AK Lampinen
Stanford University, 2020
Zero-shot task adaptation by homoiconic meta-mapping
AK Lampinen, JL McClelland
arXiv preprint arXiv:1905.09950, 2019
Improving image generative models with human interactions
AK Lampinen, D So, D Eck, F Bertsch
arXiv preprint arXiv:1709.10459, 2017
Towards mental time travel: a hierarchical memory for reinforcement learning agents
AK Lampinen, SCY Chan, A Banino, F Hill
arXiv preprint arXiv:2105.14039, 2021
Publishing fast and slow: A path toward generalizability in psychology and AI
AK Lampinen, SCY Chan, A Santoro, F Hill
PsyArXiv, 2021
Flexibility in Neural Network Models
A Lampinen, 2020
Assessing the Replicability of Psychological Science Through Pedagogy
J Arias, R Catapano, E Hermann, M Keil, A Lampinen, S Raposo, ...
What shapes feature representations? Exploring datasets, architectures, and training Download PDF
KL Hermann, AK Lampinen
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