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Deep physical neural networks trained with backpropagation

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Cited by:

  1. Hengfei Yang & Shiyuan Yang & Debiao Meng & Chenghao Hu & Chaosheng Wu & Bo Yang & Peng Nie & Yuan Si & Xiaoyan Su, 2024. "Optimization of Analog Circuit Parameters Using Bidirectional Long Short-Term Memory Coupled with an Enhanced Whale Optimization Algorithm," Mathematics, MDPI, vol. 13(1), pages 1-24, December.
  2. Jamshaid Ul Rahman & Sana Danish & Dianchen Lu, 2023. "Deep Neural Network-Based Simulation of Sel’kov Model in Glycolysis: A Comprehensive Analysis," Mathematics, MDPI, vol. 11(14), pages 1-9, July.
  3. Fan Cai & Yuesong Jiang & Wanqing Song & Kai-Hung Lu & Tongbo Zhu, 2024. "Short-Term Wind Turbine Blade Icing Wind Power Prediction Based on PCA-fLsm," Energies, MDPI, vol. 17(6), pages 1-15, March.
  4. Ruomin Zhu & Sam Lilak & Alon Loeffler & Joseph Lizier & Adam Stieg & James Gimzewski & Zdenka Kuncic, 2023. "Online dynamical learning and sequence memory with neuromorphic nanowire networks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  5. Federico Ricci & Massimiliano Avana & Francesco Mariani, 2024. "Enhancing Lambda Measurement in Hydrogen-Fueled SI Engines through Virtual Sensor Implementation," Energies, MDPI, vol. 17(16), pages 1-17, August.
  6. Gao Wang & Giulia Marcucci & Benjamin Peters & Maria Chiara Braidotti & Lars Muckli & Daniele Faccio, 2024. "Human-centred physical neuromorphics with visual brain-computer interfaces," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
  7. Shuaifeng Li & Xiaoming Mao, 2024. "Training all-mechanical neural networks for task learning through in situ backpropagation," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  8. Md Tauhidul Islam & Zixia Zhou & Hongyi Ren & Masoud Badiei Khuzani & Daniel Kapp & James Zou & Lu Tian & Joseph C. Liao & Lei Xing, 2023. "Revealing hidden patterns in deep neural network feature space continuum via manifold learning," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
  9. Malte J. Rasch & Charles Mackin & Manuel Gallo & An Chen & Andrea Fasoli & Frédéric Odermatt & Ning Li & S. R. Nandakumar & Pritish Narayanan & Hsinyu Tsai & Geoffrey W. Burr & Abu Sebastian & Vijay N, 2023. "Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
  10. Yizhi Wang & Minjia Chen & Chunhui Yao & Jie Ma & Ting Yan & Richard Penty & Qixiang Cheng, 2025. "Asymmetrical estimator for training encapsulated deep photonic neural networks," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  11. Kilian D. Stenning & Jack C. Gartside & Luca Manneschi & Christopher T. S. Cheung & Tony Chen & Alex Vanstone & Jake Love & Holly Holder & Francesco Caravelli & Hidekazu Kurebayashi & Karin Everschor-, 2024. "Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  12. Hao He & Maofeng Cao & Yun Gao & Peng Zheng & Sen Yan & Jin-Hui Zhong & Lei Wang & Dayong Jin & Bin Ren, 2024. "Noise learning of instruments for high-contrast, high-resolution and fast hyperspectral microscopy and nanoscopy," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  13. Ziyu Zhan & Hao Wang & Qiang Liu & Xing Fu, 2024. "Photonic diffractive generators through sampling noises from scattering media," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
  14. Chengkuan Gao & Prabhav Gaur & Dhaifallah Almutairi & Shimon Rubin & Yeshaiahu Fainman, 2023. "Optofluidic memory and self-induced nonlinear optical phase change for reservoir computing in silicon photonics," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
  15. Abbas, Khizar & Han, Mengyao & Xu, Deyi & Butt, Khalid Manzoor & Baz, Khan & Cheng, Jinhua & Zhu, Yongguang & Hussain, Sanwal, 2024. "Exploring synergistic and individual causal effects of rare earth elements and renewable energy on multidimensional economic complexity for sustainable economic development," Applied Energy, Elsevier, vol. 364(C).
  16. Seou Choi & Yannick Salamin & Charles Roques-Carmes & Rumen Dangovski & Di Luo & Zhuo Chen & Michael Horodynski & Jamison Sloan & Shiekh Zia Uddin & Marin Soljačić, 2024. "Photonic probabilistic machine learning using quantum vacuum noise," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
  17. Lei Tong & Yali Bi & Yilun Wang & Kai Peng & Xinyu Huang & Wei Ju & Zhuiri Peng & Zheng Li & Langlang Xu & Runfeng Lin & Xiangxiang Yu & Wenhao Shi & Hui Yu & Huajun Sun & Kanhao Xue & Qiang He & Ming, 2024. "Programmable nonlinear optical neuromorphic computing with bare 2D material MoS2," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
  18. Fangjun Hu & Saeed A. Khan & Nicholas T. Bronn & Gerasimos Angelatos & Graham E. Rowlands & Guilhem J. Ribeill & Hakan E. Türeci, 2024. "Overcoming the coherence time barrier in quantum machine learning on temporal data," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  19. Jérémie Laydevant & Danijela Marković & Julie Grollier, 2024. "Training an Ising machine with equilibrium propagation," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  20. Federico Ricci & Massimiliano Avana & Francesco Mariani, 2025. "Artificial Neural Networks as a Tool for High-Accuracy Prediction of In-Cylinder Pressure and Equivalent Flame Radius in Hydrogen-Fueled Internal Combustion Engines," Energies, MDPI, vol. 18(2), pages 1-23, January.
  21. Shi-Yuan Ma & Tianyu Wang & Jérémie Laydevant & Logan G. Wright & Peter L. McMahon, 2025. "Quantum-limited stochastic optical neural networks operating at a few quanta per activation," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
  22. Mitsumasa Nakajima & Katsuma Inoue & Kenji Tanaka & Yasuo Kuniyoshi & Toshikazu Hashimoto & Kohei Nakajima, 2022. "Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  23. Sunkyu Yu & Namkyoo Park, 2023. "Heavy tails and pruning in programmable photonic circuits for universal unitaries," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  24. Tianyu Wang & Jialin Meng & Xufeng Zhou & Yue Liu & Zhenyu He & Qi Han & Qingxuan Li & Jiajie Yu & Zhenhai Li & Yongkai Liu & Hao Zhu & Qingqing Sun & David Wei Zhang & Peining Chen & Huisheng Peng & , 2022. "Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  25. Carla Rodríguez & Sören Arlt & Leonhard Möckl & Mario Krenn, 2024. "Automated discovery of experimental designs in super-resolution microscopy with XLuminA," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  26. Hongmei Cui & Zhongyang Li & Bingchuan Sun & Teng Fan & Yonghao Li & Lida Luo & Yong Zhang & Jian Wang, 2022. "A New Ice Quality Prediction Method of Wind Turbine Impeller Based on the Deep Neural Network," Energies, MDPI, vol. 15(22), pages 1-18, November.
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