Daniel D. Lee, Ph.D.
Affiliations: | 1995-2001 | Bell Laboratories, Murray Hill, NJ, United States | |
| 2001- | Electrical and Systems Engineering | University of Pennsylvania, Philadelphia, PA, United States |
Area:
machine learning, robotics, computational neuroscience, statistical physicsWebsite:
https://www.seas.upenn.edu/~ddlee/Google:
"Daniel Dongyuel Lee" OR "Daniel D. Lee" "University of Pennsylvania"Bio:
https://www.researchgate.net/profile/Daniel_Lee27
https://scholar.google.com/citations?user=J0l7wWwAAAAJ&hl=en
Lee, Daniel Dongyuel Interfacial properties of surfactant monolayers in microemulsion systems Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1995.
Cross-listing: Neurotree - Robotree
Parents
Sign in to add mentor| Sow-Hsin Chen | grad student | 1995 | MIT (Physics Tree) | |
| (Interfacial properties of surfactant monolayers in microemulsion systems) | ||||
| Mehran Kardar | grad student | 1995 | MIT (Physics Tree) | |
| Haim Sompolinsky | research scientist | Penn (Neurotree) | ||
Children
Sign in to add trainee| Jihun Hamm | grad student | 2008 | Penn (Neurotree) |
| Yuanqing Lin | grad student | 2008 | Penn (Neurotree) |
| Paul N. Vernaza | grad student | 2011 | Penn (Neurotree) |
| Zhuo Wang | grad student | 2009-2016 | Penn (Neurotree) |
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Publications
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| Cohen U, Chung S, Lee DD, et al. (2020) Separability and geometry of object manifolds in deep neural networks. Nature Communications. 11: 746 |
| Eisen M, Zhang C, Chamon LFO, et al. (2019) Learning Optimal Resource Allocations in Wireless Systems Ieee Transactions On Signal Processing. 67: 2775-2790 |
| Lee K, Kim G, Ortega PA, et al. (2019) Bayesian optimistic Kullback–Leibler exploration Machine Learning. 108: 765-783 |
| Chung S, Cohen U, Sompolinsky H, et al. (2018) Learning Data Manifolds with a Cutting Plane Method. Neural Computation. 1-23 |
| Chung S, Lee DD, Sompolinsky H. (2018) Classification and Geometry of General Perceptual Manifolds Physical Review X. 8 |
| Noh YK, Hamm J, Park F, et al. (2017) Fluid Dynamic Models for Bhattacharyya-based Discriminant Analysis. Ieee Transactions On Pattern Analysis and Machine Intelligence |
| Wang Z, Stocker AA, Lee DD. (2016) Efficient Neural Codes That Minimize Lp Reconstruction Error. Neural Computation. 1-31 |
| Chung S, Lee DD, Sompolinsky H. (2016) Linear readout of object manifolds. Physical Review. E. 93: 060301 |
| Lee DD, Ortega PA, Stocker AA. (2014) Dynamic belief state representations. Current Opinion in Neurobiology. 25: 221-7 |
| Wang Z, Stocker AA, Lee DD. (2013) Fisher-optimal neural population codes for high-dimensional diffeomorphic stimulus representations Advances in Neural Information Processing Systems |