Daniel Yamins
Daniel Yamins
Assistant Professor of Computer Science and Psychology, Stanford University
Verified email at stanford.edu - Homepage
Cited by
Cited by
Performance-optimized hierarchical models predict neural responses in higher visual cortex
DLK Yamins, H Hong, CF Cadieu, EA Solomon, D Seibert, JJ DiCarlo
Proceedings of the National Academy of Sciences 111 (23), 8619-8624, 2014
Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
J Bergstra, D Yamins, DD Cox
Jmlr, 2013
Using goal-driven deep learning models to understand sensory cortex
DLK Yamins, JJ DiCarlo
Nature neuroscience 19 (3), 356, 2016
Deep neural networks rival the representation of primate IT cortex for core visual object recognition
CF Cadieu, H Hong, DLK Yamins, N Pinto, D Ardila, EA Solomon, ...
PLoS Comput Biol 10 (12), e1003963, 2014
Explicit information for category-orthogonal object properties increases along the ventral stream
H Hong, DLK Yamins, NJ Majaj, JJ DiCarlo
Nature neuroscience 19 (4), 613, 2016
Dynamic Task Assignment in Robot Swarms.
J McLurkin, D Yamins
Robotics: Science and Systems 8 (2005), 2005
A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy
AJE Kell, DLK Yamins, EN Shook, SV Norman-Haignere, JH McDermott
Neuron 98 (3), 630-644. e16, 2018
Hierarchical modular optimization of convolutional networks achieves representations similar to macaque IT and human ventral stream
DL Yamins, H Hong, C Cadieu, JJ DiCarlo
Advances in neural information processing systems, 3093-3101, 2013
Growing urban roads
D Yamins, S Rasmussen, D Fogel
Networks and Spatial Economics 3 (1), 69-85, 2003
Identification and functional validation of the novel antimalarial resistance locus PF10_0355 in Plasmodium falciparum
D Van Tyne, DJ Park, SF Schaffner, DE Neafsey, E Angelino, JF Cortese, ...
PLoS genetics 7 (4), 2011
Flexible neural representation for physics prediction
D Mrowca, C Zhuang, E Wang, N Haber, LF Fei-Fei, J Tenenbaum, ...
Advances in neural information processing systems, 8799-8810, 2018
A theory of local-to-global algorithms for one-dimensional spatial multi-agent systems
D Yamins
A dissertation presented to the School of Engineering and Applied Sciences …, 2007
Task-driven convolutional recurrent models of the visual system
A Nayebi, D Bear, J Kubilius, K Kar, S Ganguli, D Sussillo, JJ DiCarlo, ...
Advances in Neural Information Processing Systems, 5290-5301, 2018
A deep learning framework for neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature neuroscience 22 (11), 1761-1770, 2019
Towards a theory of" local to global" in distributed multi-agent systems (I)
D Yamins
Proceedings of the fourth international joint conference on Autonomous …, 2005
Brain-score: Which artificial neural network for object recognition is most brain-like?
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ...
BioRxiv, 407007, 2018
Automated global-to-local programming in 1-d spatial multi-agent systems
D Yamins, R Nagpal
Proceedings of the 7th international joint conference on Autonomous agents …, 2008
Learning to play with intrinsically-motivated, self-aware agents
N Haber, D Mrowca, S Wang, LF Fei-Fei, DL Yamins
Advances in Neural Information Processing Systems, 8388-8399, 2018
StarFlow: A script-centric data analysis environment
E Angelino, D Yamins, M Seltzer
International Provenance and Annotation Workshop, 236-250, 2010
Local aggregation for unsupervised learning of visual embeddings
C Zhuang, AL Zhai, D Yamins
Proceedings of the IEEE International Conference on Computer Vision, 6002-6012, 2019
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