PHI Lab Publications

Noether’s Learning Dynamics: Role of Symmetry Breaking in Neural Networks

Hidenori Tanaka, Daniel Kunin

NeurIPS 2021 (Advances in Neural Information Processing Systems)

https://arxiv.org/abs/2105.02716

Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning

Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka

NeurIPS 2021 (Advances in Neural Information Processing Systems)

https://arxiv.org/abs/2106.05956

Efficient simulation of ultrafast quantum nonlinear optics with matrix product states

Ryotatsu Yanagimoto, Edwin Ng, Logan G. Wright, Tatsuhiro Onodera, and Hideo Mabuchi

Optica, 8 (10) 1306-1315 (2021)

https://arxiv.org/abs/2102.05902

Hardware error correction for programmable photonics

Saumil Bandyopadhyay, Ryan Hamerly, and Dirk Englund

Optica 8 (10) 1247-1255 (2021)

https://arxiv.org/abs/2103.04993

Coherent Ising Machines with Optical Error Correction Circuits

Sam Reifenstein, Satoshi Kako, Farad Khoyratee, Timothée Leleu, Yoshihisa Yamamoto

Adv. Quantum Technol. 2021, 2100077

https://arxiv.org/abs/2108.07369

Dispersion-engineered χ(2) nanophotonics: a flexible tool for nonclassical light

Marc Jankowski, Jatadhari Mishra and M. M. Fejer

Journal of Physics Photonics 3 (4)

https://arxiv.org/abs/2103.02296

The Future of Deep Learning Is Photonic: Reducing the energy needs of neural networks might require computing with light

Ryan Hamerly

IEEE Spectrum 58 (7) 2021