Magnetohydrodynamics with physics informed neural operators von Shawn G Rosofsky, E A Huerta

“… Machine Learning: Science and Technology …”
Volltext

Stochastic gradient descent with random label noises: doubly stochastic models and inference stabilizer von Haoyi Xiong, Xuhong Li, Boyang Yu, Dongrui Wu, Zhanxing Zhu, Dejing Dou

“… Machine Learning: Science and Technology …”
Volltext

Multi-target quantum compilation algorithm von Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja, Nguyen Vu Linh, Lan Nguyen Tran, Le Bin Ho

“… Machine Learning: Science and Technology …”
Volltext

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose est... von Jhansi Rani Challapalli, Nagaraju Devarakonda

“… Machine Learning: Science and Technology …”
Volltext

Beware of diffusion models for synthesizing medical images—a comparison with GANs in terms of memorizing brain MRI and chest x-ray images von Muhammad Usman Akbar, Wuhao Wang, Anders Eklund

“… Machine Learning: Science and Technology …”
Volltext

A study of transfer learning in digital rock properties measurement von M I K Haq, I N Yulita, I A Dharmawan

“… Machine Learning: Science and Technology …”
Volltext

Neural network field theories: non-Gaussianity, actions, and locality von Mehmet Demirtas, James Halverson, Anindita Maiti, Matthew D Schwartz, Keegan Stoner

“… Machine Learning: Science and Technology …”
Volltext

Machine learning inspired models for Hall effects in non-collinear magnets von Jonathan Kipp, Fabian R Lux, Thorben Pürling, Abigail Morrison, Stefan Blügel, Daniele Pinna, Yuriy Mokrousov

“… Machine Learning: Science and Technology …”
Volltext

Unification of symmetries inside neural networks: transformer, feedforward and neural ODE von Koji Hashimoto, Yuji Hirono, Akiyoshi Sannai

“… Machine Learning: Science and Technology …”
Volltext

Neural network Gaussian processes as efficient models of potential energy surfaces for polyatomic molecules von J Dai, R V Krems

“… Machine Learning: Science and Technology …”
Volltext

Online meta-learned gradient norms for active learning in science and technology von Haiqi Dong, Amanda S Barnard, Amanda J Parker

“… Machine Learning: Science and Technology …”
Volltext

Reducing training data needs with minimal multilevel machine learning (M3L) von Stefan Heinen, Danish Khan, Guido Falk von Rudorff, Konstantin Karandashev, Daniel Jose Arismendi Arrieta, Alastair J A Price, Surajit Nandi, Arghya Bhowmik, Kersti Hermansson, O Anatole von Lilienfeld

“… Machine Learning: Science and Technology …”
Volltext

From STEM-EDXS data to phase separation and quantification using physics-guided NMF von Adrien Teurtrie, Nathanaël Perraudin, Thomas Holvoet, Hui Chen, Duncan T L Alexander, Guillaume Obozinski, Cécile Hébert

“… Machine Learning: Science and Technology …”
Volltext

ATSFCNN: a novel attention-based triple-stream fused CNN model for hyperspectral image classification von Jizhen Cai, Clotilde Boust, Alamin Mansouri

“… Machine Learning: Science and Technology …”
Volltext

CAD system for epileptic seizure detection from EEG through image processing and SURF-BOF technique von Mohammad H Alshayeji

“… Machine Learning: Science and Technology …”
Volltext

An exponentially-growing family of universal quantum circuits von Mo Kordzanganeh, Pavel Sekatski, Leonid Fedichkin, Alexey Melnikov

“… Machine Learning: Science and Technology …”
Volltext

Efficient determination of the Hamiltonian and electronic properties using graph neural network with complete local coordinates von Mao Su, Ji-Hui Yang, Hong-Jun Xiang, Xin-Gao Gong

“… Machine Learning: Science and Technology …”
Volltext

Quantum resources of quantum and classical variational methods von Thomas Spriggs, Arash Ahmadi, Bokai Chen, Eliska Greplova

“… Machine Learning: Science and Technology …”
Volltext

Deep learning representations for quantum many-body systems on heterogeneous hardware von Xiao Liang, Mingfan Li, Qian Xiao, Junshi Chen, Chao Yang, Hong An, Lixin He

“… Machine Learning: Science and Technology …”
Volltext

Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function von Jiawei Zang, Matija Medvidović, Dominik Kiese, Domenico Di Sante, Anirvan M Sengupta, Andrew J Millis

“… Machine Learning: Science and Technology …”
Volltext