Christopher J. Cueva
Christopher J. Cueva
Stanford University, Columbia University, MIT
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Cited by
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Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
CJ Cueva, XX Wei
International Conference on Learning Representations (ICLR), 2018
Dynamics of neural population responses in prefrontal cortex indicate changes of mind on single trials
R Kiani, CJ Cueva, JB Reppas, WT Newsome
Current Biology 24 (13), 1542-1547, 2014
full-FORCE: A target-based method for training recurrent networks
B DePasquale, CJ Cueva, K Rajan, GS Escola, LF Abbott
PloS one 13 (2), e0191527, 2018
Low-dimensional dynamics for working memory and time encoding
CJ Cueva, A Saez, E Marcos, A Genovesio, M Jazayeri, R Romo, ...
Proceedings of the National Academy of Sciences 117 (37), 23021-23032, 2020
Natural grouping of neural responses reveals spatially segregated clusters in prearcuate cortex
R Kiani, CJ Cueva, JB Reppas, D Peixoto, SI Ryu, WT Newsome
Neuron 85 (6), 1359-1373, 2015
Visual perception as retrospective Bayesian decoding from high-to low-level features
S Ding, CJ Cueva, M Tsodyks, N Qian
Proceedings of the National Academy of Sciences 114 (43), E9115-E9124, 2017
Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks
CJ Cueva, PY Wang, M Chin, XX Wei
International Conference on Learning Representations (ICLR Spotlight), 2019
NeuroGym: An open resource for developing and sharing neuroscience tasks
M Molano-Mazon, J Barbosa, J Pastor-Ciurana, M Fradera, RUY ZHANG, ...
PsyArXiv, 2022
Emergent neural dynamics and geometry for generalization in a transitive inference task
K Kay, N Biderman, R Khajeh, M Beiran, CJ Cueva, D Shohamy, ...
PLOS Computational Biology 20 (4), e1011954, 2024
Recurrent neural network models for working memory of continuous variables: activity manifolds, connectivity patterns, and dynamic codes
CJ Cueva, A Ardalan, M Tsodyks, N Qian
arXiv preprint arXiv:2111.01275, 2021
Natural constraints explain working memory capacity limitations in sensory-cognitive models
Y Xie, Y Duan, A Cheng, P Jiang, CJ Cueva, GR Yang
bioRxiv, 2023.03. 30.534982, 2023
Differentiable optimization of similarity scores between models and brains
N Cloos, M Siegel, SL Brincat, EK Miller, CJ Cueva
ICLR 2024 Workshop on Representational Alignment, 2024
Scaling up the Evaluation of Recurrent Neural Network Models for Cognitive Neuroscience
N Cloos, M Li, GR Yang, CJ Cueva
Cognitive Computational Neuroscience, 2022
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