Emerging role of machine learning in light-matter interaction

Pushing the limits of optical information storage using deep learning

(2019) Peter R. Wiecha et al.   Nature Nanotechnology

Efficient spectrum prediction and inverse design for plasmonic waveguide systems based on artificial neural networks

(2019) Tian Zhang et al.   Photonics Research

Net-FLICS: fast quantitative wide-field fluorescence lifetime imaging with compressed sensing – a deep learning approach

(2019) Ruoyang Yao et al.   Light-Science & Applications

Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning

(2019) Yair Rivenson et al.   Nature Biomedical Engineering

Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials

(2018) Wei Ma et al.   ACS Nano

Prediction and understanding of AIE effect by quantum mechanics-aided machine-learning algorithm

(2018) Jia Qiu et al.   CHEMICAL COMMUNICATIONS

Physics-informed machine learning for inorganic scintillator discovery

(2018) G. Pilania et al.   JOURNAL OF CHEMICAL PHYSICS

Predicting the Band Gaps of Inorganic Solids by Machine Learning

(2018) Ya Zhuo et al.   Journal of Physical Chemistry Letters

Deep learning massively accelerates super-resolution localization microscopy

(2018) Wei Ouyang et al.   NATURE BIOTECHNOLOGY

Learning atoms for materials discovery

(2018) Quan Zhou et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep-STORM: super-resolution single-molecule microscopy by deep learning

(2018) Elias Nehme et al.   Optica

Nanophotonic particle simulation and inverse design using artificial neural networks

(2018) John Peurifoy et al.   Science Advances

Generative Model for the Inverse Design of Metasurfaces

(2018) Zhaocheng Liu et al.   NANO LETTERS

Intelligent identification of two-dimensional nanostructures by machine-learning optical microscopy

(2018) Xiaoyang Lin et al.   Nano Research

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning

(2018) Shuaihua Lu et al.   Nature Communications

Plasmonic nanostructure design and characterization via Deep Learning

(2018) Itzik Malkiel et al.   Light-Science & Applications

Deep learning enables cross-modality super-resolution in fluorescence microscopy

(2018) Hongda Wang et al.   NATURE METHODS

Optimization of photonic crystal nanocavities based on deep learning

(2018) Takashi Asano et al.   OPTICS EXPRESS

Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction

(2017) Baichuan Sun et al.   Journal of Chemical Information and Modeling

Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond

(2017) Arun Mannodi-Kanakkithodi et al.   Materials Today

Phase recovery and holographic image reconstruction using deep learning in neural networks

(2017) Yair Rivenson et al.   Light-Science & Applications

Deep learning microscopy

(2017) Yair Rivenson et al.   Optica

Machine-learning-assisted materials discovery using failed experiments

(2016) Paul Raccuglia et al.   NATURE

Machine learning bandgaps of double perovskites

(2016) G. Pilania et al.   Scientific Reports