Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
Steven Tsan, Raghav Kansal, Anthony Aportela et al.
Data Analysis papers — page 24
physics.data-anBrowse archive
Explaining machine-learned particle-flow reconstruction
Farouk Mokhtar, Raghav Kansal, Daniel Diaz et al.Correlations between Panoramic Imagery and Gamma-Ray Background in an Urban Area
M. S. Bandstra, B. J. Quiter, M. Salathe et al.Phase reconstruction from oscillatory data with iterated Hilbert transform embeddings -- benefits and limitations
Erik Gengel, Arkady PikovskyImproved algorithms for determination of particle directions with Timepix3
Petr Mánek, Benedikt Bergmann, Petr Burian et al.A novel parameter for nonequilibrium analysis in reconstructed state spaces
Wenpo Yao, Wenli Yao, Jun WangIdentification of the nature of dynamical systems with recurrence plots and convolution neural networks: A preliminary test
Daniel Han, Giuseppe Orlando, Sergei FedotovNuclear data evaluation with Bayesian networks
Georg Schnabel, Roberto Capote, Arjan Koning et al.Vibrational quality classification of metallic turbine blades under measurement uncertainty
Liangliang Cheng, Vahid Yaghoubi, Wim V. Paepegem et al.Corrupted bifractal features in finite uncorrelated power-law distributed data
Felipe Olivares, Massimiliano ZaninFourier-domain transfer entropy spectrum
Yang Tian, Yaoyuan Wang, Ziyang Zhang et al.Wind Farm Icing Loss Forecast Pertinent to Winter Extremes
Linyue Gao, Teja Dasari, Jiarong HongStochastic approach for assessing the predictability of chaotic time series using reservoir computing
Igor A KhovanovUniversal uncertainty estimation for nuclear detector signals with neural networks and ensemble learning
Pengcheng Ai, Zhi Deng, Yi Wang et al.Dynamical effects of inflation in ensemble-based data assimilation under the presence of model error
Scheffler Guillermo, Carrassi Alberto, Ruiz Juan et al.NoLiTiA: An Open-Source Toolbox for Nonlinear Time Series Analysis
Immo Weber, Carina Renate OehrnParadigm Shift Through the Integration of Physical Methodology and Data Science
Takashi MiyamotoSparse Data Generation for Particle-Based Simulation of Hadronic Jets in the LHC
Breno Orzari, Thiago Tomei, Maurizio Pierini et al.Grassmannian diffusion maps based surrogate modeling via geometric harmonics
Ketson R. M. dos Santos, Dimitrios G. Giovanis, Katiana Kontolati et al.Inferring the shape of data: A probabilistic framework for analyzing experiments in the natural sciences
Korak Kumar Ray, Anjali R. Verma, Ruben L. Gonzalez et al.Extreme events in dynamical systems and random walkers: A review
Sayantan Nag Chowdhury, Arnob Ray, Syamal K. Dana et al.Generalized Poincar\'e Orthogonality: A New Approach to POLSAR Data Analysis
Shane R. Cloude, Ashlin RichardsonAriadne: PyTorch Library for Particle Track Reconstruction Using Deep Learning
Pavel Goncharov, Egor Schavelev, Anastasia Nikolskaya et al.Solving an elastic inverse problem using Convolutional Neural Networks
Nachiket H. GokhaleApplication of Deep Learning Technique to an Analysis of Hard Scattering Processes at Colliders
Lev Dudko, Petr Volkov, Georgii Vorotnikov et al.