Kimberly Lauren Stachenfeld
Kimberly Lauren Stachenfeld
Research Scientist, DeepMind
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The hippocampus as a predictive map
KL Stachenfeld, MM Botvinick, SJ Gershman
Nature neuroscience 20 (11), 1643-1653, 2017
What is a cognitive map? Organizing knowledge for flexible behavior
TEJ Behrens, TH Muller, JCR Whittington, S Mark, AB Baram, ...
Neuron 100 (2), 490-509, 2018
Design principles of the hippocampal cognitive map
KL Stachenfeld, M Botvinick, SJ Gershman
Advances in neural information processing systems 27, 2528-2536, 2014
Structured agents for physical construction
V Bapst, A Sanchez-Gonzalez, C Doersch, K Stachenfeld, P Kohli, ...
International Conference on Machine Learning, 464-474, 2019
Noradrenergic control of error perseveration in medial prefrontal cortex
MS Caetano, LE Jin, L Harenberg, KL Stachenfeld, AFT Arnsten, ...
Frontiers in integrative neuroscience 6, 125, 2013
A general model of hippocampal and dorsal striatal learning and decision making
JP Geerts, F Chersi, KL Stachenfeld, N Burgess
Proceedings of the National Academy of Sciences 117 (49), 31427-31437, 2020
A probabilistic approach to discovering dynamic full-brain functional connectivity patterns
JR Manning, X Zhu, TL Willke, R Ranganath, K Stachenfeld, U Hasson, ...
NeuroImage 180, 243-252, 2018
Spectral inference networks: Unifying deep and spectral learning
D Pfau, S Petersen, A Agarwal, DGT Barrett, KL Stachenfeld
arXiv preprint arXiv:1806.02215, 2018
Jraph: A library for graph neural networks in jax., 2020
J Godwin, T Keck, P Battaglia, V Bapst, T Kipf, Y Li, K Stachenfeld, ...
URL http://github. com/deepmind/jraph, 0
Flexible modulation of sequence generation in the entorhinal–hippocampal system
DC McNamee, KL Stachenfeld, MM Botvinick, SJ Gershman
Nature Neuroscience 24 (6), 851-862, 2021
The hippocampus as a predictive map. bioRxiv, 097170
KL Stachenfeld, MM Botvinick, SJ Gershman
Formalizing planning and information search in naturalistic decision-making
LT Hunt, ND Daw, P Kaanders, MA MacIver, U Mugan, E Procyk, ...
Nature neuroscience 24 (8), 1051-1064, 2021
Probabilistic successor representations with Kalman temporal differences
JP Geerts, KL Stachenfeld, N Burgess
arXiv preprint arXiv:1910.02532, 2019
Learning neural representations that support efficient reinforcement learning
K Stachenfeld
Princeton University, 2018
Graph Networks with Spectral Message Passing
K Stachenfeld, J Godwin, P Battaglia
arXiv preprint arXiv:2101.00079, 2020
Object-oriented state editing for HRL
V Bapst, A Sanchez-Gonzalez, O Shams, K Stachenfeld, PW Battaglia, ...
arXiv preprint arXiv:1910.14361, 2019
Author Correction: The hippocampus as a predictive map
KL Stachenfeld, MM Botvinick, SJ Gershman
Nature neuroscience 21 (6), 895-895, 2018
Learned Coarse Models for Efficient Turbulence Simulation
K Stachenfeld, DB Fielding, D Kochkov, M Cranmer, T Pfaff, J Godwin, ...
arXiv preprint arXiv:2112.15275, 2021
Interpretable Deep Learning for Computational Fluid Dynamics
M Cranmer, C Cui, D Fielding, A Sanchez-Gonzalez, K Stachenfeld, ...
Bulletin of the American Physical Society 66, 2021
Training spectral inference neural networks using bilevel optimization
DB Pfau, S Petersen, A Agarwal, D Barrett, K Stachenfeld
US Patent App. 16/972,491, 2021
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