Shared representational geometry across neural networks.
Lu, Q., Chen, P. H., Pillow, J. W., Ramadge, P. J., Norman, K. A., & Hasson, U.
Workshop on Integration of Deep Learning Theories, NeurIPS 2018.
poster, paper, demo
BrainIAK education: user-friendly tutorials for advanced, computationally-intensive fMRI analysis.
Kumar, M., Ellis, C. T., Lu, Q., Zhang, H., Ramadge P. J., Norman, K. A., & Turk-Browne N. B.
Poster presented at the Annual Meeting of the Society for Neuroscience, SfN 2018.
Performance optimization is insufficient for building accurate models for neural representation.
Yu, J., Lu, Q., Hasson, U., Norman, K. A., & Pillow, J. W.
The Conference on Cognitive Computational Neuroscience, CCN 2018.
Measuring representational similarity across neural networks.
Lu, Q., Ramadge, P., Norman, K. A., & Hasson, U.
Poster presented at the Annual Meeting of the Cognitive Science Society, CogSci 2018.
Undergrad works / before 2017
An interactive model accounts for both ultra-rapid superordinate classification and basic-level advantage in object recognition.
Lu, Q., & Rogers, T. T.
Poster presented at the Annual Meeting of the Cognitive Science Society, CogSci 2016.
Teaching a neural network to count: reinforcement learning with "social scaffolding".
Lu, Q., & McClelland, J. L.
Poster presented at the Neural Computation and Psychology Workshop, NCPW 2016.
Iterative Lasso: An even-handed approach to whole brain multivariate pattern analysis.
Cox, C. R., Lu, Q., & Rogers, T. T.
Poster presented at the Cognitive Neuroscience Society conference, CNS 2015.
Poster presented at the Neuroimaging, Computational Neuroscience and Neuroengineering Workshop, Madison, WI., 2015.
A Parallel-Distributed Processing Approach to Mathematical Cognition.
McClelland, J. L., Mickey, K., Hansen, S., Yuan, X., & Lu, Q. (2016).