Results 171 to 180 of about 221,728 (275)

Fast ground irradiance computations for agrivoltaics via physics-informed deep learning models. [PDF]

Commun Eng
Kurumundayil L, Burkhardt D, Gfüllner L, Rupitsch SJ, Preu R, Berwind M, Demant M.   +6 more
europepmc   +1 more source

Quantitative Analysis of Fluorescent Sensor Arrays

Analysis &Sensing, EarlyView.
Fluorescent sensor arrays have great potential for the quantification of analytes in complex systems. Herein, statistical multivariate techniques and deep learning models to provide quantitative information from such arrays are reviewed. Fluorescent sensor arrays address the limitations of a single sensor by leveraging multiple sensing elements to ...
Karandeep Grover, Muhammad Tahir Waseem, Haobo Guo, Elizabeth J. New   +3 more
wiley   +1 more source

ADBM: Adversarial Diffusion Bridge Model for Denoising of 3D Point Cloud Data. [PDF]

Sensors (Basel)
Nam C, Lee SJ.
europepmc   +1 more source

The Achilles’ Heel of Competitive/Adversarial Systems [PDF]

, 2011
openaire   +1 more source

Harnessing Machine Learning and Deep Learning Approaches for Laser‐Induced Breakdown Spectroscopy Data Analysis: A Comprehensive Review

Analysis &Sensing, EarlyView.
Laser‐induced breakdown spectroscopy (LIBS), an atomic emission technique, is widely applied in fields like geology and biology. This rapid elemental analysis method leverages computational tools to boost precision and speed up data processing. This review explores machine learning and deep learning methods for analyzing LIBS spectral data, tackling ...
Pegah Dehbozorgi, Ludovic Duponchel, Vincent Motto‐Ros, Thomas Bocklitz   +3 more
wiley   +1 more source

Penalized GANs with latent perturbation for robust shilling attack generation in recommender systems. [PDF]

Discov Comput
Nawara D, Kashef R.
europepmc   +1 more source

Latent Diffusion Models for Virtual Battery Material Screening and Characterization

Batteries &Supercaps, EarlyView.
A newly developed virtual tool is designed to enhance the extraction of meaningful information from characterization technique data and effectively guides the screening of target battery materials based on functional requirements. Efficient characterization of battery materials is fundamental to understanding the underlying electrochemical mechanisms ...
Deepalaxmi Rajagopal, Arnd Koeppe, Adrian Cierpka, Britta Nestler   +3 more
wiley   +1 more source

Investigating whether deep learning models for co-folding learn the physics of protein-ligand interactions. [PDF]

Nat Commun
Masters MR, Mahmoud AH, Lill MA.
europepmc   +1 more source

Mining Chemical Space with Generative Models for Battery Materials

Batteries &Supercaps, EarlyView.
Revolutionizing Li‐ion battery material discovery with MatterGen, a foundational generative AI model for crystal structure inverse design. Explored stable, unique, and novel compositions and their analysis with respect to the state‐of‐the‐art databases, followed by DFT validation, provides a new direction for accelerating materials discovery ...
Chiku Parida, Diptendu Roy, Juan Maria García Lastra, Arghya Bhowmik   +3 more
wiley   +1 more source

Diversity-enhanced reconstruction as plug-in defenders against adversarial perturbations. [PDF]

Front Artif Intell
Pang Z, Yan X, Guo S, Lu Y.
europepmc   +1 more source