[1] N. Engheta. Thin absorbing screens using metamaterial surfaces. IEEE Antennas and Propagation Society International Symposium, 392-395(2002).

[2] N. I. Landy, S. Sajuyigbe, J. J. Mock, D. R. Smith, W. J. Padilla. Perfect metamaterial absorber. Phys. Rev. Lett., 100, 207402(2008).

[3] M. Diem, T. Koschny, C. M. Soukoulis. Wide-angle perfect absorber/thermal emitter in the terahertz regime. Phys. Rev. B, 79, 033101(2009).

[4] A. Vora, J. Gwamuri, N. Pala, A. Kulkarni, J. M. Pearce, D. Ö. Güney. Exchanging ohmic losses in metamaterial absorbers with useful optical absorption for photovoltaics. Sci. Rep., 4, 4901(2014).

[5] F. B. Barho, F. Gonzalez-Posada, M. Bomers, A. Mezy, L. Cerutti, T. Taliercio. Surface-enhanced thermal emission spectroscopy with perfect absorber metasurfaces. ACS Photon., 6, 1506-1514(2019).

[6] N. Liu, M. Mesch, T. Weiss, M. Hentschel, H. Giessen. Infrared perfect absorber and its application as plasmonic sensor. Nano Lett., 10, 2342-2348(2010).

[7] H. Tao, C. Bingham, D. Pilon, K. Fan, A. Strikwerda, D. Shrekenhamer, W. Padilla, X. Zhang, R. Averitt. A dual band terahertz metamaterial absorber. J. Phys. D, 43, 225102(2010).

[8] J. Hao, J. Wang, X. Liu, W. J. Padilla, L. Zhou, M. Qiu. High performance optical absorber based on a plasmonic metamaterial. Appl. Phys. Lett., 96, 251104(2010).

[9] P. Bouchon, C. Koechlin, F. Pardo, R. Hadar, J.-L. Pelouard. Wideband omnidirectional infrared absorber with a patchwork of plasmonic nanoantennas. Opt. Lett., 37, 1038-1040(2012).

[10] K. Chen, R. Adato, H. Altug. Dual-band perfect absorber for multispectral plasmon-enhanced infrared spectroscopy. ACS Nano, 6, 7998-8006(2012).

[11] J. Xu, Z. Zhao, H. Yu, L. Yang, P. Gou, J. Cao, Y. Zou, J. Qian, T. Shi, Q. Ren, Z. An. Design of triple-band metamaterial absorbers with refractive index sensitivity at infrared frequencies. Opt. Express, 24, 25742-25751(2016).

[12] J. W. Park, P. Van Tuong, J. Y. Rhee, K. W. Kim, W. H. Jang, E. H. Choi, L. Y. Chen, Y. Lee. Multi-band metamaterial absorber based on the arrangement of donut-type resonators. Opt. Express, 21, 9691-9702(2013).

[13] Y. Ma, Q. Chen, J. Grant, S. C. Saha, A. Khalid, D. R. Cumming. A terahertz polarization insensitive dual band metamaterial absorber. Opt. Lett., 36, 945-947(2011).

[14] S. Liu, H. Chen, T. J. Cui. A broadband terahertz absorber using multi-layer stacked bars. Appl. Phys. Lett., 106, 151601(2015).

[15] Z. Zhang, Z. Yu, Y. Liang, T. Xu. Dual-band nearly perfect absorber at visible frequencies. Opt. Mater. Express, 8, 463-468(2018).

[16] G. Dayal, S. A. Ramakrishna. Design of multi-band metamaterial perfect absorbers with stacked metal–dielectric disks. J. Opt., 15, 055106(2013).

[17] W. Ma, Z. Liu, Z. A. Kudyshev, A. Boltasseva, W. Cai, Y. Liu. Deep learning for the design of photonic structures. Nat. Photonics, 15, 77-90(2021).

[18] K. Yao, R. Unni, Y. Zheng. Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale. Nanophotonics, 8, 339-366(2019).

[19] S. So, T. Badloe, J. Noh, J. Rho, J. Bravo-Abad. Deep learning enabled inverse design in nanophotonics. Nanophotonics, 9, 1041-1057(2020).

[20] J. Peurifoy, Y. Shen, L. Jing, Y. Yang, F. Cano-Renteria, B. G. DeLacy, J. D. Joannopoulos, M. Tegmark, M. Soljačić. Nanophotonic particle simulation and inverse design using artificial neural networks. Sci. Adv., 4, eaar4206(2018).

[21] D. Liu, Y. Tan, E. Khoram, Z. Yu. Training deep neural networks for the inverse design of nanophotonic structures. ACS Photon., 5, 1365-1369(2018).

[22] S. So, J. Mun, J. Rho. Simultaneous inverse design of materials and structures via deep learning: demonstration of dipole resonance engineering using core–shell nanoparticles. ACS Appl. Mater. Interfaces, 11, 24264-24268(2019).

[23] Z. Liu, D. Zhu, S. P. Rodrigues, K.-T. Lee, W. Cai. Generative model for the inverse design of metasurfaces. Nano Lett., 18, 6570-6576(2018).

[24] S. So, J. Rho. Designing nanophotonic structures using conditional deep convolutional generative adversarial networks. Nanophotonics, 8, 1255-1261(2019).

[25] Y. Kiarashinejad, M. Zandehshahvar, S. Abdollahramezani, O. Hemmatyar, R. Pourabolghasem, A. Adibi. Knowledge discovery in nanophotonics using geometric deep learning. Adv. Intell. Syst., 2, 1900132(2020).

[26] W. Ma, F. Cheng, Y. Liu. Deep-learning-enabled on-demand design of chiral metamaterials. ACS Nano, 12, 6326-6334(2018).

[27] J. Frankle, M. Carbin. The lottery ticket hypothesis: finding sparse, trainable neural networks(2018).

[28] D. Blalock, J. J. G. Ortiz, J. Frankle, J. Guttag. What is the state of neural network pruning?(2020).

[29] M. Babaeizadeh, P. Smaragdis, R. H. Campbell. Noiseout: a simple way to prune neural networks(2016).