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200 papers

Modern data-driven machine learning system designs exploit inductive biases in architectural structure, invariance and equivariance requirements, task-specific loss functions, and computational optimization tools. Previous works have…

Neural and Evolutionary Computing · Computer Science 2025-03-04 Achref Jaziri , Sina Ditzel , Iuliia Pliushch , Visvanathan Ramesh

We present Helmlab, a family of two purpose-built color spaces for UI design systems sharing a common 11-stage analytical structure: MetricSpace, a 72-parameter space optimized for color-difference prediction, and GenSpace, a 44-parameter…

Graphics · Computer Science 2026-05-07 Gorkem Yildiz

Metasurfaces with spatially varying subwavelength structures enable full control of electromagnetic waves over a wide spectrum. High-efficiency metasurfaces, especially in a transmission mode, are of practical significance in optical…

Inverse materials design has proven successful in accelerating novel material discovery. Many inverse materials design methods use unsupervised learning where a latent space is learned to offer a compact description of materials…

Machine Learning · Computer Science 2026-02-11 Cheng Zeng , Zulqarnain Khan , Nathan L. Post

Optical imaging below the limit of light diffraction offers an unprecedented opportunity to study outlook, organization, interactions or in-situ functioning of sub-micrometer, highly transparent objects such as subcellular structures in…

Very long baseline interferometry (VLBI) achieves the highest angular resolution in astronomy. VLBI measures corrupted Fourier components, known as visibilities. Reconstructing on-sky images from these visibilities is a challenging inverse…

Instrumentation and Methods for Astrophysics · Physics 2025-11-25 Paul Tiede , William Moses , Valentin Churavy , Michael D. Johnson , Dominic Pesce , Lindy Blackburn , Peter Galison

Ill-posed inverse problems in imaging remain an active research topic in several decades, with new approaches constantly emerging. Recognizing that the popular dictionary learning and convolutional sparse coding are both essentially…

Image and Video Processing · Electrical Eng. & Systems 2019-10-25 Zhuonan He , Jinjie Zhou , Dong Liang , Yuhao Wang , Qiegen Liu

Deep learning is a promising, ultra-fast approach for inverse design in nano-optics, but despite fast advancement of the field, the computational cost of dataset generation, as well as of the training procedure itself remains a major…

Optical multilayer thin film structures have been widely used in numerous photonic domains and applications. The key component to enable these applications is the inverse design. Different from other photonic structures such as metasurface…

Optics · Physics 2024-09-27 Taigao Ma , Mingqian Ma , L. Jay Guo

3D additive manufacturing enables the fabrication of nanophotonic structures with subwavelength features that control light across macroscopic scales. Gradient-based optimization offers an efficient approach to design these complex and…

Inverse design of metasurfaces for the joint optimization of optical modulation and algorithmic decoding in computational optics presents significant challenges, especially in applications such as hyperspectral imaging. We introduce a…

Image and Video Processing · Electrical Eng. & Systems 2025-10-28 Rongzhou Chen , Haitao Nie , Shuo Zhu , Yaping Zhao , Chutian Wang , Edmund Y. Lam

Nanophotonic technologies inherently rely on tailoring light-matter interactions through the excitation and interference of deeply confined optical resonances. However, existing concepts in optical mode engineering remain heuristic and are…

Inverse-designed Silicon photonic metastructures offer an efficient platform to perform analog computations with electromagnetic waves. However, due to computational difficulties, scaling up these metastructures to handle a large number of…

The capability of holography to project three-dimensional (3D) images and correct for aberrations offers much potential to enhance optical control in light-based 3D printing. Notably, multi-beam multi-wavelength holographic systems…

Optics · Physics 2024-01-30 Chi Chung Li , Joseph Toombs , Vivek Subramanian , Hayden K. Taylor

Over the past two decades, photonic inverse design has emerged as a powerful approach to implement photonic devices with improved performance, or realize new functionalities. While the efforts over the first decade focused on proof of…

Optics · Physics 2026-02-24 Louise Schul , Sydney Mason , Sungjun Eun , Geun Ho Ahn , Jelena Vučković

Inverse design represents a paradigm shift in the development of nanophotonic devices, where optimal geometries and materials are discovered by an algorithm rather than symmetry considerations or intuition. Here we present a very general…

Quantum Physics · Physics 2020-04-29 Robert Bennett , Stefan Yoshi Buhmann

An ultimate goal of materials science is to deliver materials with desired properties at will. In the theoretical study, a standard approach consists of constructing a Hamiltonian based on phenomenology or first principles, calculating…

Strongly Correlated Electrons · Physics 2023-03-24 Koji Inui , Yukitoshi Motome

A deep learning-based wavelength controllable forward prediction and inverse design model of nanophotonic devices is proposed. Both the target time-domain and wavelength-domain information can be utilized simultaneously, which enables…

Optics · Physics 2020-11-09 Yuchen Song , Danshi Wang , Han Ye , Jun Qin , Min Zhang

We propose a free-space, inverse design of nanostructure's effective mode-matching fields via a backward propagation of tightly focused vector beams to the pupil plane of an aplanatic system of high numerical aperture. First, we study the…

Optics · Physics 2022-10-25 Xiaorun Zang , Ari T. Friberg , Tero Setälä , Jari Turunen

The high complexity of various inverse problems poses a significant challenge to model-based reconstruction schemes, which in such situations often reach their limits. At the same time, we witness an exceptional success of data-based…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 T. A. Bubba , G. Kutyniok , M. Lassas , M. März , W. Samek , S. Siltanen , V. Srinivasan