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 physics
Website:
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.

Mean distance: 14.81 (cluster 17)
 
SNBCP
Cross-listing: Robotree - E-Tree

Parents

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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

Children

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Jihun Hamm grad student 2008 Penn
Yuanqing Lin grad student 2008 Penn
Paul N. Vernaza grad student 2011 Penn
Zhuo Wang grad student 2009-2016 Penn
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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
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