Saxe, Andrew

A deep learning framework for neuroscience

Richards, B. A., Lillicrap, T. P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., Clopath, C., Costa, R. P., de Berker, A., Ganguli, S., et al. (2019) · Nature Neuroscience

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 1,027

If deep learning is the answer, what is the question?

Saxe, A., Nelli, S., & Summerfield, C. (2021) · Nature Reviews Neuroscience

Neural dynamics and brain functionNeural Networks and Applications

Cited by 397

Qualitatively characterizing neural network optimization problems

Goodfellow, I. J., Vinyals, O., & Saxe, A. M. (2014) · arXiv

Stochastic Gradient Optimization TechniquesNeural Networks and Applications

Cited by 341

A mathematical theory of semantic development in deep neural networks

Saxe, A. M., McClelland, J. L., & Ganguli, S. (2019) · Proceedings of the National Academy of Sciences

Neural Networks and ApplicationsCategorization, perception, and language

Cited by 284

Organizing memories for generalization in complementary learning systems

Sun, W., Advani, M., Spruston, N., Saxe, A., & Fitzgerald, J. E. (2023) · Nature Neuroscience

Memory and Neural MechanismsMemory Processes and Influences

Cited by 103