IOP出版社7月精选文章——Machine Learning/AI&Climate Change and Cities

精选文章

Machine Learning/AI

2D Materials

Understanding domain reconstruction of twisted transition metal dichalcogenide bilayers through machine learned interatomic potentials

A Siddiqui, C Xu, S J Magorrian and N D M Hine

Fine tuning generative adversarial networks with universal force fields: application to two-dimensional topological insulators

Alexander C Tyner

Superconductor Science and Technology

Critical current density prediction in high temperature superconducting tapes using transformer-based deep learning

Jiyuan Gao, Hongye Zhang, Chenxuan Zhang, Jiafu Wei, Qian Dong, Mingzhe Sang and Markus Mueller

Estimation of magnetic levitation and lateral forces in MgB₂ superconducting bulks with various dimensional sizes using artificial intelligence techniques

Shahin Alipour Bonab, Yiteng Xing, Giacomo Russo, Massimo Fabbri, Antonio Morandi, Pierre Bernstein, Jacques Noudem and Mohammad Yazdani-Asrami

Journal of Physics: Condensed Matter

MLIPX: machine-learned interatomic potential eXploration

Fabian Zills, Sheena Agarwal, Tiago J Goncalves, Srishti Gupta, Edvin Fako, Shuang Han, Imke Britta Mueller, Christian Holm and Sandip De

Machine-learning interatomic potential for BaTiO₃: phase transitions, domain walls, and grain boundaries

Amit Sehrawat, Karsten Albe and Jochen Rohrer

Journal of Physics: Complexity

Bounded graph clustering with graph neural networks

Kibidi Neocosmos, Diego Baptista and Nicole Ludwig

How do probabilistic graphical models and graph neural networks look at network data?

Michela Lapenna and Caterina De Bacco

A hybrid deep learning model for human mobility prediction

Erjian Liu, Xingjian Wang, Ying Wang, Dan Zhao, Xuejun Niu and Xin Lu

Classical and Quantum Gravity

Long short-term memory for early warning detection of gravitational waves

Reem Alfaidi and Christopher Messenger

Intelligent gravitational wave detection with pulsar timing array using complex-valued convolutional neural network

Linkang Wang, Jin Liu, Xin Ma, Xiaolin Ning and Qifeng Hou

Machine Learning: Science and Technology

Inferring measure synchronization in coupled bosonic Josephson junctions with reservoir computing

Han Zhang, Huawei Fan, Haibo Qiu, Jianlong Qiu, Xiangyong Chen, Qingguo Xiao and Xingang Wang

Continuous SUN (stable, unique, and novel) metric for generative modeling of inorganic crystals

Masahiro Negishi, Hyunsoo Park, Kinga Oliwia Mastej and Aron Walsh

Regularity priors for the linear atomic cluster expansion

James P Darby, Joe D Morrow, Albert P Bartók, Volker L Deringer, Gábor Csányi and Christoph Ortner

AtomProNet: data flow to and from machine learning interatomic potentials in materials science

Musanna Galib, Mewael Isiet and Mauricio Ponga

Pushing the limits of unconstrained machine-learned interatomic potentials

Filippo Bigi, Paolo Pegolo, Arslan Mazitov, Jonathan Schmidt and Michele Ceriotti

Journal of Physics D: Applied Physics

Machine learning applications to computational plasma physics and reduced-order plasma modeling: a perspective

Farbod Faraji and Maryam Reza

Machine learning-based estimator for electron impact ionization fragmentation patterns

Kateryna M Lemishko, Gregory S J Armstrong, Sebastian Mohr, Anna Nelson, Jonathan Tennyson and Peter J Knowles

Climate Change and Cities

Journal of Physics: Complexity

Influence of model selection on optimal control of traffic for emissions minimisation

Khatun E Zannat, Judith Y T Wang and David P Watling

Optimizing taxi operations in Shanghai for reduced idle time and greener transportation: a spatiotemporal analysis using trajectory data and complex networks

Zhanxin Ma, Zhangyi Ye, Xinyue Sun, Bin Pan, Haobo Ni and Yixiu Kong

Environmental Research Letters

Weather hazards in cities of East Asia: interacting influences of global warming and urbanization

Jiacan Yuan, Yuanhao Chen, Jian Hang, Eun-Soon IM, Qiqi Luo, Josipa Milovac and Lei Zhao

Environmental Research: Infrastructure and Sustainability

Tracking green space along streets of world cities

Giacomo Falchetta and Ahmed T Hammad

Environmental Research: Climate

Urban heat in global cities and the role of nature-based solutions in mitigating future climate risks

Manuel Esperon-Rodriguez, Rachael V Gallagher, Jonathan Lenoir, Victor L Barradas, Linda J Beaumont, Carlo Calfapietra, Paloma Cariñanos, Stephen J Livesley, Tamara Iungma, Gabriele Manoli, Renee M Marchin, Timon McPhearson, Christian Messier, Mark Nieuwenhuijsen, Sally A Power, Paul D Rymer and Mark G Tjoelker

Machine Learning: Earth

A deep learning bias-correction layer for land surface models: application to soil moisture during drought and hurricane events

Mahmoud Mbarak, Manmeet Singh, Naveen Sudharsan and Zong-Liang Yang

How far can we downscale? Resolution limits and physical interpretability of diffusion models for African precipitation

Jangho Lee and Sara Shamekh

An interpretable latent space reveals changing dynamics of European heatwaves

Tamara Happé, Jasper S Wijnands, Paolo Scussolini, Peter Pfleiderer and Dim Coumou

Predictability of precipitation extremes in the Western United States and the U.S. Gulf Coast using AI weather models

Anton Petry, Weiming Hu and Alpaslan Yörük

Spatial deep learning for PM2.5 estimation during extreme pollution events: Quantifying uncertainty and training with sparse datasets

Shijin Wei, Kyle Shores, Yu-Sheng Chen and Yangyang Xu