| Training deep neural networks for the inverse design of nanophotonic structures D Liu, Y Tan, E Khoram, Z Yu Acs Photonics 5 (4), 1365-1369, 2018 | 863 | 2018 |
| Nanophotonic media for artificial neural inference E Khoram, A Chen, D Liu, L Ying, Q Wang, M Yuan, Z Yu Photonics Research 7 (8), 823-827, 2019 | 140 | 2019 |
| A bidirectional deep neural network for accurate silicon color design L Gao, X Li, D Liu, L Wang, Z Yu Advanced Materials 31 (51), 1905467, 2019 | 138 | 2019 |
| Inverse design of metasurfaces based on coupled-mode theory and adjoint optimization M Zhou, D Liu, SW Belling, H Cheng, MA Kats, S Fan, ML Povinelli, Z Yu Acs Photonics 8 (8), 2265-2273, 2021 | 64 | 2021 |
| Self-focused thermal emission and holography realized by mesoscopic thermal emitters M Zhou, E Khoram, D Liu, B Liu, S Fan, ML Povinelli, Z Yu ACS Photonics 8 (2), 497-504, 2021 | 21 | 2021 |
| Real-time deep learning design tool for far-field radiation profile J Qie, E Khoram, D Liu, M Zhou, L Gao Photonics Research 9 (4), B104-B108, 2021 | 19 | 2021 |
| ACS Photonics 5, 1365 (2018) D Liu, Y Tan, E Khoram, Z Yu Article CAS, 0 | 9 | |
| Edge transport bifurcation in plasma resistive interchange turbulence B Li, XY Wang, CK Sun, C Meng, A Zhou, D Liu Physics of Plasmas 24 (5), 2017 | 8 | 2017 |
| Bifurcation and hysteresis of plasma edge transport in a flux-driven system B Li, XY Wang, CK Sun, A Zhou, D Liu, CH Ma, XG Wang Physical Review E 94 (4), 043201, 2016 | 8 | 2016 |
| Magnetic curvature effects on plasma interchange turbulence B Li, X Liao, CK Sun, W Ou, D Liu, G Gui, XG Wang Physics of Plasmas 23 (6), 2016 | 5 | 2016 |
| Deep neural networks: a bidirectional deep neural network for accurate silicon color design (adv. Mater. 51/2019) L Gao, X Li, D Liu, L Wang, Z Yu Advanced Materials 31 (51), 1970364, 2019 | 4 | 2019 |
| Optimization of Nonlinear Nanophotonic Media for Artificial Neural Inference E Khoram, A Chen, D Liu, Q Wang, M Yuan, Z Yu CLEO: Applications and Technology, JM3M. 4, 2019 | 2 | 2019 |
| Stochastic optimization of nonlinear nanophotonic media for artificial neural inference E Khoram, A Chen, D Liu, Q Wang, Z Yu arXiv preprint arXiv:1810.07815, 2018 | 2 | 2018 |
| The Application of Machine Learning for Designing and Controlling Electromagnetic Fields D Liu The University of Wisconsin-Madison, 2021 | 1 | 2021 |
| Examination of pairs in neutrino mixing matrix D Liu, BQ Ma Physical Review D 92 (3), 033011, 2015 | 1 | 2015 |
| Spontaneous emergence of eyes in reinforcement learning agents D Liu, B Liu, M Zhou, Y Qu, Z Wu, Q Zhou, Z Yu | | 2023 |
| Nonlinear Nanophotonic Media for Artificial Neural Computing E Khoram, A Chen, D Liu, Q Wang, M Yuan, Z Yu 2019 IEEE Research and Applications of Photonics in Defense Conference …, 2019 | | 2019 |
| Transition Dynamics and Hysteresis of Plasma Edge Transport in a Flux-driven System X Wang, C Sun, A Zhou, D Liu, B Li, X Wang APS Division of Plasma Physics Meeting Abstracts 2016, UP10. 026, 2016 | | 2016 |
Zongfu YuProfessor of Electrical and Computer Engineering, University of Wisconsin - MadisonVerified email at wisc.edu
