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ORCIDMachine Learning: Science and Technology, Volume 4
Volume 4, Number 1, March 2023
- Pablo Lemos
, Miles D. Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho:
Robust simulation-based inference in cosmology with Bayesian neural networks. 01 - Simone Ciarella, Jeanne Trinquier, Martin Weigt, Francesco Zamponi:
Machine-learning-assisted Monte Carlo fails at sampling computationally hard problems. 10501 - Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu:
Material transformers: deep learning language models for generative materials design. 15001 - Alexandre Boulle, A Debelle:
Convolutional neural network analysis of x-ray diffraction data: strain profile retrieval in ion beam modified materials. 15002 - Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan:
Learning the dynamics of particle-based systems with Lagrangian graph neural networks. 15003 - Muhammad Kashif, Saif M. Al-Kuwari:
The impact of cost function globality and locality in hybrid quantum neural networks on NISQ devices. 15004 - Tobias Haug, Chris N. Self, M. S. Kim:
Quantum machine learning of large datasets using randomized measurements. 15005 - Gunhee Park, Joonsuk Huh, Daniel K. Park:
Variational quantum one-class classifier. 15006 - Abdulhakim Alnuqaydan, Sergei Gleyzer, Harrison Prosper:
SYMBA: symbolic computation of squared amplitudes in high energy physics with machine learning. 15007 - Petr Mánek, Graham W. Van Goffrier, Vignesh Gopakumar, Nikolaos Nikolaou, Jonathan Shimwell, Ingo P. Waldmann:
Fast regression of the tritium breeding ratio in fusion reactors. 15008 - Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui:
Noise-aware physics-informed machine learning for robust PDE discovery. 15009 - Yongqiang Cheng, Geoffrey Wu, Daniel M. Pajerowski, Matthew B. Stone, Andrei T. Savici, Mingda Li, Anibal Ramirez-Cuesta:
Direct prediction of inelastic neutron scattering spectra from the crystal structure. 15010 - Arpan Biswas, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin:
Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *. 15011 - Artan Sheshmani, Yi-Zhuang You, Wenbo Fu, Ahmadreza Azizi:
Categorical representation learning and RG flow operators for algorithmic classifiers. 15012 - Chandrajit Bajaj, Luke McLennan, Timothy Andeen, Avik Roy:
Recipes for when physics fails: recovering robust learning of physics informed neural networks. 15013 - Alexander Luce, Ali Mahdavi, Heribert Wankerl, Florian Marquardt:
Investigation of inverse design of multilayer thin-films with conditional invertible neural networks. 15014 - Marco Corrias, Lorenzo Papa, Igor Sokolovic, Viktor Birschitzky, Alexander Gorfer, Martin Setvin, Michael Schmid, Ulrike Diebold, Michele Reticcioli, Cesare Franchini:
Automated real-space lattice extraction for atomic force microscopy images. 15015 - Dmitri Iouchtchenko, Jérôme F. Gonthier, Alejandro Perdomo-Ortiz, Roger G. Melko:
Neural network enhanced measurement efficiency for molecular groundstates. 15016 - Varun Shankar, Vedant Puri, Ramesh Balakrishnan, Romit Maulik, Venkatasubramanian Viswanathan:
Differentiable physics-enabled closure modeling for Burgers' turbulence. 15017 - Christyan Cruz Ulloa, Luis Garrido, Jaime del Cerro, Antonio Barrientos:
Autonomous victim detection system based on deep learning and multispectral imagery. 15018 - Elisabetta Cornacchia, Francesca Mignacco, Rodrigo Veiga, Cédric Gerbelot, Bruno Loureiro, Lenka Zdeborová:
Learning curves for the multi-class teacher-student perceptron. 15019 - Sascha Klawohn, James R. Kermode, Albert P. Bartók:
Massively parallel fitting of Gaussian approximation potentials. 15020 - Chris Tennant, Brian Freeman, Reza Kazimi, Daniel Moser, Dan T. Abell, Jonathan P. Edelen, Joshua Einstein-Curtis:
A smart alarm for particle accelerator beamline operations. 15021 - Brendan Folie, Maxwell Hutchinson:
Multivariate prediction intervals for bagged models. 15022 - Stefano Mensa, Mustafa Emre Sahin, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Ivano Tavernelli:
Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage. 15023 - Horacio Olivares-Pilón, Adrian M. Escobar-Ruiz, Mario Alan Quiroz-Juárez, Norberto Aquino:
Confined hydrogen atom: endohedrals H@C36 and H@C60. 15024 - Laura Gambini, Tiarnan Mullarkey, Lewys Jones, Stefano Sanvito:
Machine-learning approach for quantified resolvability enhancement of low-dose STEM data. 15025 - Shoummo Ahsan Khandoker, Jawaril Munshad Abedin, Mohamed Hibat-Allah:
Supplementing recurrent neural networks with annealing to solve combinatorial optimization problems. 15026 - Joshua A. Rackers, Lucas Tecot, Mario Geiger, Tess E. Smidt:
A recipe for cracking the quantum scaling limit with machine learned electron densities. 15027 - Tingting Xue, Xu Li, Xiaosong Chen, Li Chen, Zhangang Han:
Machine learning phases in swarming systems. 15028 - Assaf Shmuel, Eyal Heifetz:
Developing novel machine-learning-based fire weather indices. 15029 - Mehmet Akif Özdemir, Gizem Dilara Ozdemir, Merve Gul, Onan Güren, Utku Kursat Ercan:
Machine learning to predict the antimicrobial activity of cold atmospheric plasma-activated liquids. 15030 - Truong Son Hy, Risi Kondor:
Multiresolution equivariant graph variational autoencoder. 15031 - Min-Ruei Lin, Wan-Ju Li, Shin-Ming Huang:
Quaternion-based machine learning on topological quantum systems. 15032 - Lakshmi Revathi Krosuri, Aravapalli Rama Satish:
Novel heuristic-based hybrid ResNeXt with recurrent neural network to handle multi class classification of sentiment analysis. 15033 - Chang Min Hyun, Tae Jun Jang, Jeongchan Nam, Hyeuknam Kwon, Kiwan Jeon, Kyounghun Lee:
Machine learning-based signal quality assessment for cardiac volume monitoring in electrical impedance tomography. 15034 - Xiao Liang, Mingfan Li, Qian Xiao, Junshi Chen, Chao Yang, Hong An, Lixin He:
Deep learning representations for quantum many-body systems on heterogeneous hardware. 15035 - K. M. Abubeker, S. Baskar:
B2-Net: an artificial intelligence powered machine learning framework for the classification of pneumonia in chest x-ray images. 15036 - Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo:
Predicting thermoelectric transport properties from composition with attention-based deep learning. 15037
Volume 4, Number 2, June 2023
- S. V. Venkatakrishnan, Chris M. Fancher, Maxim A. Ziatdinov, Rama K. Vasudevan, Kyle Saleeby, James Haley, Dunji Yu, Ke An, Alex Plotkowski:
Adaptive sampling for accelerating neutron diffraction-based strain mapping *. 25001 - Jingzu Yee, Daichi Igarashi, Shun Miyatake, Yoshiyuki Tagawa:
Prediction of the morphological evolution of a splashing drop using an encoder-decoder. 25002 - Junyu Liu, Changchun Zhong, Matthew Otten, Anirban Chandra, Cristian L. Cortes, Chaoyang Ti, Stephen K. Gray, Xu Han:
Quantum Kerr learning. 25003 - Elham E Khoda, Dylan S. Rankin, Rafael Teixeira de Lima, Philip C. Harris, Scott Hauck, Shih-Chieh Hsu, Michael Kagan, Vladimir Loncar, Chaitanya Paikara, Richa Rao, Sioni Summers, Caterina Vernieri, Aaron Wang:
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. 25004 - Carlotta Trigila, Anirudh Srikanth, Emilie Roncali:
A generative adversarial network to speed up optical Monte Carlo simulations. 25005 - Davide Piras, Hiranya V. Peiris, Andrew Pontzen, Luisa Lucie-Smith, Ningyuan Guo, Brian Nord:
A robust estimator of mutual information for deep learning interpretability. 25006 - Samuel Duffield, Marcello Benedetti, Matthias Rosenkranz:
Bayesian learning of parameterised quantum circuits. 25007 - Insoo Kim, Minhyeok Lee, Junhee Seok:
ICEGAN: inverse covariance estimating generative adversarial network. 25008 - Lars Dingeldein, Pilar Cossio, Roberto Covino:
Simulation-based inference of single-molecule force spectroscopy. 25009 - Simone Ciarella, Massimiliano Chiappini, Emanuele Boattini, Marjolein Dijkstra, Liesbeth M. C. Janssen:
Dynamics of supercooled liquids from static averaged quantities using machine learning. 25010 - Aydin Göze Polat, Ferda Nur Alpaslan:
The reusability prior: comparing deep learning models without training. 25011 - Ana Larrañaga, Steven L. Brunton, Javier Martínez, Sergio Chapela, Jacobo Porteiro:
Data-driven prediction of the performance of enhanced surfaces from an extensive CFD-generated parametric search space. 25012 - Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild:
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. 25013 - Patrick Emami, Aidan Perreault, Jeffrey N. Law, David Biagioni, Peter C. St. John:
Plug & play directed evolution of proteins with gradient-based discrete MCMC. 25014 - Jhansi Rani Challapalli, Nagaraju Devarakonda:
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 estimation. 25015 - Francesco Velotti, Brennan Goddard, Verena Kain, Rebecca Louise Ramjiawan, Giovanni Zevi Della Porta, Simon Hirlaender:
Towards automatic setup of 18 MeV electron beamline using machine learning. 25016 - Jan Weinreich, Guido Falk von Rudorff, O. Anatole von Lilienfeld:
Encrypted machine learning of molecular quantum properties. 25017 - Said Ouala, Bertrand Chapron, Fabrice Collard, Lucile Gaultier, Ronan Fablet:
Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework. 25018 - Cameron J. Gruich, Varun Madhavan, Yixin Wang, Bryan R. Goldsmith:
Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification. 25019 - Yongcheng Ding, Xi Chen, José Rafael Magdalena Benedicto, José D. Martín-Guerrero:
Closed-loop control of a noisy qubit with reinforcement learning. 25020
Volume 4, Number 3, September 2023
- Jakub Rydzewski, Ming Chen, Omar Valsson:
Manifold learning in atomistic simulations: a conceptual review. 31001 - Gang Seob Jung, Hunjoo Myung, Stephan Irle:
Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals **. 35001 - Shawn G. Rosofsky, Eliu A. Huerta:
Magnetohydrodynamics with physics informed neural operators. 35002 - Ayush Khot, Mark S. Neubauer, Avik Roy:
A detailed study of interpretability of deep neural network based top taggers. 35003 - Emiliano Diaz, Gherardo Varando, Juan Emmanuel Johnson, Gustau Camps-Valls:
Learning latent functions for causal discovery. 35004 - Valerio Briganti, Alessandro Lunghi:
Efficient generation of stable linear machine-learning force fields with uncertainty-aware active learning. 35005 - Shampa Raghunathan, Sai Ajay Kashyap Nakirikanti:
Intramolecular proton transfer reaction dynamics using machine-learned ab initio potential energy surfaces. 35006 - Tobias Schanz, Klas Ove Möller, Saskia Rühl, David S. Greenberg:
Robust detection of marine life with label-free image feature learning and probability calibration. 35007 - Harpreet Kaur, Thomas Franosch, Michele Caraglio:
Adaptive active Brownian particles searching for targets of unknown positions. 35008 - Javier Lopez-Piqueres, Jing Chen, Alejandro Perdomo-Ortiz:
Symmetric tensor networks for generative modeling and constrained combinatorial optimization. 35009 - Mao Su, Ji-Hui Yang, Hongjun Xiang, Xingao Gong:
Efficient determination of the Hamiltonian and electronic properties using graph neural network with complete local coordinates. 35010 - Michael J. Williams, John Veitch, Chris Messenger:
Importance nested sampling with normalising flows. 35011 - Nicholas M. Boffi, Eric Vanden-Eijnden:
Probability flow solution of the Fokker-Planck equation. 35012 - Eric Lin, Boyuan Liu, Leann Lac, Daryl L. X. Fung, Carson K. Leung, Pingzhao Hu:
scGMM-VGAE: a Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data. 35013 - Miruna T. Cretu, Alessandra Toniato, Amol Thakkar, Amin A Debabeche, Teodoro Laino, Alain C. Vaucher:
Standardizing chemical compounds with language models. 35014 - Harbir Antil, Howard C. Elman, Akwum Onwunta, Deepanshu Verma:
A deep neural network approach for parameterized PDEs and Bayesian inverse problems. 35015 - Florian B. Hinz, Amr H. Mahmoud, Markus A. Lill:
Prediction of molecular field points using SE(3)-transformer model. 35016 - Odilon Duranthon, Lenka Zdeborová:
Neural-prior stochastic block model. 35017 - Thomas Templin, Milad Memarzadeh, Walter Vinci, Paul Aaron Lott, Ata Akbari Asanjan, Anthony Alexiades Armenakas, Eleanor Gilbert Rieffel:
Anomaly detection in aeronautics data with quantum-compatible discrete deep generative model. 35018 - Dongjin Lee, Seong-Heon Lee, Jae-Hun Jung:
The effects of topological features on convolutional neural networks - an explanatory analysis via Grad-CAM. 35019 - Ouail Kitouni, Niklas Nolte, Mike Williams:
Robust and provably monotonic networks. 35020 - Sandy Adhitia Ekahana, Genta Indra Winata, Y. Soh, Anna Tamai, Radovic Milan, Gabriel Aeppli, Ming Shi:
Transfer learning application of self-supervised learning in ARPES. 35021 - Jun Yang, James Whitfield:
Machine-learning Kohn-Sham potential from dynamics in time-dependent Kohn-Sham systems. 35022 - Adam Wunderlich, Jack Sklar:
Data-driven modeling of noise time series with convolutional generative adversarial networks ∗. 35023 - Philippe Bacon, Agata Trovato, Michal Bejger:
Denoising gravitational-wave signals from binary black holes with a dilated convolutional autoencoder. 35024 - Simon Axelrod, Rafael Gómez-Bombarelli:
Molecular machine learning with conformer ensembles. 35025 - Song Jin Ri, Pavel Putrov:
Graph Neural Networks and 3-dimensional topology. 35026 - Maxwell T. West, Martin Sevior, Muhammad Usman:
Reflection equivariant quantum neural networks for enhanced image classification. 35027 - Sonja Grönroos, Maurizio Pierini, Nadezda Chernyavskaya:
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier. 35028 - Gaia Grosso, Nicolò Lai, Marco Letizia, Jacopo Pazzini, Marco Rando, Lorenzo Rosasco, Andrea Wulzer, Marco Zanetti:
Fast kernel methods for data quality monitoring as a goodness-of-fit test. 35029 - Guojing Cong, Victor Fung:
Improving materials property predictions for graph neural networks with minimal feature engineering *. 35030 - Joshua A. Vita, Daniel Schwalbe-Koda:
Data efficiency and extrapolation trends in neural network interatomic potentials. 35031 - Sofia-Paraskevi Moschou, Elliot Hicks, R. Y. Parekh, D. Mathew, S. Majumdar, Nektarios Vlahakis:
Physics-informed neural networks for modeling astrophysical shocks. 35032 - Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová:
Error scaling laws for kernel classification under source and capacity conditions. 35033 - M. I K. Haq, Intan Nurma Yulita, I A Dharmawan:
A study of transfer learning in digital rock properties measurement. 35034 - Gregory A. Daly, Jonathan E. Fieldsend, Graham Hassall, Gavin R. Tabor:
Data-driven plasma modelling: surrogate collisional radiative models of fluorocarbon plasmas from deep generative autoencoders. 35035 - Mohammad Kordzanganeh, Pavel Sekatski, Leonid Fedichkin, Alexey Melnikov:
An exponentially-growing family of universal quantum circuits. 35036 - Eyal Rozenberg, Daniel Freedman:
Semi-equivariant conditional normalizing flows, with applications to target-aware molecule generation. 35037 - Iulian Emil Tampu, Neda Haj-Hosseini, Ida Blystad, Anders Eklund:
Deep learning-based detection and identification of brain tumor biomarkers in quantitative MR-images. 35038 - Peter Wirnsberger, Borja Ibarz, George Papamakarios:
Estimating Gibbs free energies via isobaric-isothermal flows. 35039 - Samuel Tovey, Sven Krippendorf, Konstantin Nikolaou, Christian Holm:
Towards a phenomenological understanding of neural networks: data. 35040 - Dileep Kumar Soother, Manuel Domínguez Pumar, Elisa Sayrol-Clols, Josefina Torres, Mercedes Marín, Javier Gómez-Elvira, Luis Mora, Sara Navarro, José Antonio Rodríguez Manfredi:
Improving resilience of sensors in planetary exploration using data-driven models. 35041 - Anton Charkin-Gorbulin, Kyle Cranmer, Francesco Armando Di Bello, Etienne Dreyer, Sanmay Ganguly, Eilam Gross, Lukas Heinrich, Marumi Kado, Nilotpal Kakati, Patrick Rieck, Lorenzo Santi, Matteo Tusoni:
Configurable calorimeter simulation for AI applications. 35042 - Lea M. Trenkwalder, Andrea López-Incera, Hendrik Poulsen Nautrup, Fulvio Flamini, Hans J. Briegel:
Automated gadget discovery in the quantum domain. 35043 - Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, Katja Krüger, Peter McKeown, Lennart Rustige:
New angles on fast calorimeter shower simulation. 35044 - Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, Wolfgang Wenzel, Pascal Friederich:
Interpretable delta-learning of GW quasiparticle energies from GGA-DFT. 35045 - Adrian Radu, Carlos A Duque:
Deep learning neural network for approaching Schrödinger problems with arbitrary two-dimensional confinement. 35046 - Zhao-Min Chen, Xin Jin, Xiaoqin Zhang, Chaoqun Xia, Zhiyong Pan, Ruoxi Deng, Jie Hu, Heng Chen:
DIM: long-tailed object detection and instance segmentation via dynamic instance memory. 35047 - Nina Baldy, Nicolas Simon, Viktor K. Jirsa, Meysam Hashemi:
Hierarchical Bayesian pharmacometrics analysis of Baclofen for alcohol use disorder. 35048 - Archis S. Joglekar, Alexander G. R. Thomas:
Machine learning of hidden variables in multiscale fluid simulation. 35049 - Sebastian Falkner, Alessandro Coretti, Salvatore Romano, Phillip L. Geissler, Christoph Dellago:
Conditioning Boltzmann generators for rare event sampling. 35050
Volume 4, Number 4, December 2023
- Josua Faller, Narbota Amanova, Ruben E. van Engen, Jörg Martin, Clemens Elster:
About the generalizability of deep learning based image quality assessment in mammography. 45001 - Pablo Lemos, Niall Jeffrey, Miles D. Cranmer, Shirley Ho, Peter W. Battaglia:
Rediscovering orbital mechanics with machine learning. 45002 - Senwei Liang, Aditya N. Singh, Yuanran Zhu, David T. Limmer, Chao Yang:
Probing reaction channels via reinforcement learning. 45003