- Bayesian Surrogate Analysis and Uncertainty Propagation
2021/01/11 by Ranftl, Sascha, von der Linden, Wolfgang · 3 citations
#Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Methodology (stat.ME) #Statistics and Probability (physics.data-an)
- A Digital Quantum Algorithm for Jet Clustering in High-Energy Physics
2021/01/11 by Diogo Pires, Pires, Diogo, P. Bargassa +5 · 1 citation
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #Data Analysis #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Particle physics theoretical and experimental studies #Quantum Computing Algorithms and Architecture #Statistics and Probability (physics.data-an)
- New insights on the reinforced Elephant Random Walk using a martingale approach
2020/12/29 by Lucile Laulin, Laulin, Lucile · 1 citation
Mathematics · #Data Analysis #FOS: Mathematics #FOS: Physical sciences #Markov Chains and Monte Carlo Methods #Probability (math.PR) #Random Matrices and Applications #Statistics and Probability (physics.data-an) #Stochastic processes and statistical mechanics
- Ptychographic wavefront characterisation for single-particle imaging at X-ray lasers
2020/12/26 by Benedikt J. Daurer, S. Sala, Daurer, Benedikt J. +29 · 1 citation
Physics and Astronomy · #Advanced X-ray Imaging Techniques #Astrophysical Phenomena and Observations #Data Analysis #FOS: Physical sciences #Laser-Plasma Interactions and Diagnostics #Optics (physics.optics) #Statistics and Probability (physics.data-an)
- Quantum Convolutional Neural Networks for High Energy Physics Data Analysis
2020/12/22 by Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chen, Samuel Yen-Chi +6 · 17 citations
Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Computational Physics and Python Applications #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG) #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #Quantum Physics (quant-ph) #Statistics and Probability (physics.data-an)
- Unsupervised in-distribution anomaly detection of new physics through conditional density estimation
2020/12/21 by Stein, George, Seljak, Uros, Dai, Biwei · 3 citations
#Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG) #Statistics and Probability (physics.data-an)
- Image-Based Jet Analysis
2020/12/17 by M. Kagan, Kagan, Michael · 2 citations
Computer Science · Engineering · #Aerodynamics and Acoustics in Jet Flows #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics and Turbulent Flows #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Machine Learning (cs.LG) #Statistics and Probability (physics.data-an)
- Particle Track Reconstruction using Geometric Deep Learning
2020/12/15 by Yogesh Verma, Verma, Yogesh, S. Jena +1 · 2 citations
Physics and Astronomy · #Astrophysics and Cosmic Phenomena #Dark Matter and Cosmic Phenomena #Data Analysis #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Particle Detector Development and Performance #Statistics and Probability (physics.data-an)
- Machine learning prediction of critical transition and system collapse
2020/12/02 by Ling-Wei Kong, Kong, Ling-Wei, Huawei Fan +5 · 11 citations
Computer Science · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Artificial Intelligence (cs.AI) #Data Analysis #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Neural Networks and Reservoir Computing #Statistics and Probability (physics.data-an) #stochastic dynamics and bifurcation
- Lookahead optimizer improves the performance of Convolutional Autoencoders for reconstruction of natural images
2020/12/03 by Sayan Nag, Nag, Sayan · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Generative Adversarial Networks and Image Synthesis #Graphics (cs.GR) #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Medical Image Segmentation Techniques #Statistics and Probability (physics.data-an)
- Deploying deep learning in OpenFOAM with TensorFlow
2020/12/01 by Maulik, Romit, Sharma, Himanshu, Patel, Saumil +2 · 1 citation
#Computational Physics (physics.comp-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG) #Statistics and Probability (physics.data-an)
- Weighted network motifs as random walk patterns
2020/12/02 by Francesco Picciolo, Picciolo, Francesco, Franco Ruzzenenti +5 · 1 citation
Economics, Econometrics and Finance · Environmental Science · Physics and Astronomy · #Applications (stat.AP) #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an) #Sustainability and Ecological Systems Analysis
- Separating Mesoscale and Submesoscale Flows from Clustered Drifter Trajectories
2020/12/01 by Oscroft, Sarah, Sykulski, Adam M., Early, Jeffrey J. · 1 citation
#Applications (stat.AP) #Atmospheric and Oceanic Physics (physics.ao-ph) #Data Analysis #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Signal Processing (eess.SP) #Statistics and Probability (physics.data-an) #electronic engineering #information engineering
- Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics
2020/11/25 by Vasudevan, Rama K., Kelley, Kyle, Hinkle, Jacob +4 · 2 citations
#Data Analysis #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Statistics and Probability (physics.data-an)
- Sensitivity optimization of multichannel searches for new signals
2020/11/23 by G. Punzi, Punzi, Giovanni · 1 citation
Computer Science · Physics and Astronomy · #Data Analysis #Experimental and Theoretical Physics Studies #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #High Energy Physics - Experiment (hep-ex) #Methodology (stat.ME) #Statistics and Probability (physics.data-an)
- First-passage times to quantify and compare structural correlations and heterogeneity in complex systems
2020/11/12 by Aleix Bassolas, Vincenzo Nicosia, Bassolas, Aleix +1 · 2 citations
Economics, Econometrics and Finance · Physics and Astronomy · #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Data Analysis #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Statistical Mechanics (cond-mat.stat-mech) #Statistics and Probability (physics.data-an)
- Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
2020/11/11 by Maxime Vandegar, Vandegar, Maxime, M. Kagan +5 · 7 citations
Computer Science · Engineering · Physics and Astronomy · #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Nuclear reactor physics and engineering #Statistics and Probability (physics.data-an)
- Deep learning architectures for inference of AC-OPF solutions
2020/11/06 by Thomas Falconer, Falconer, Thomas, Letif Mones +1 · 1 citation
Engineering · #Data Analysis #Electric Power System Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Machine Learning (cs.LG) #Optimal Power Flow Distribution #Power System Reliability and Maintenance #Signal Processing (eess.SP) #Statistics and Probability (physics.data-an) #Systems and Control (eess.SY) #electronic engineering #information engineering
- Machine Learning Climate Model Dynamics: Offline versus Online Performance
2020/11/05 by Noah Brenowitz, Brian Henn, Brenowitz, Noah D. +13 · 2 citations
Earth and Planetary Sciences · Engineering · Environmental Science · #Atmospheric and Oceanic Physics (physics.ao-ph) #Climate variability and models #Data Analysis #Energy Load and Power Forecasting #FOS: Physical sciences #Meteorological Phenomena and Simulations #Statistics and Probability (physics.data-an)
- Accuracy and precision of the estimation of the number of missing levels in chaotic spectra using long-range correlations
2020/11/03 by I. Casal, Casal, I., Luís Múñoz +3 · 2 citations
Chemistry · Physics and Astronomy · #Chaos control and synchronization #Data Analysis #FOS: Physical sciences #Molecular spectroscopy and chirality #Nuclear Theory (nucl-th) #Other Condensed Matter (cond-mat.other) #Quantum Physics (quant-ph) #Quantum chaos and dynamical systems #Statistics and Probability (physics.data-an)
- Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
2020/10/26 by Marc Finzi, Ke Alexander Wang, Finzi, Marc +3 · 11 citations
Computer Science · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #Control and Stability of Dynamical Systems #Data Analysis #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Modeling and Simulation Systems #Neural Networks and Applications #Statistics and Probability (physics.data-an) #Time Series Analysis and Forecasting
- Global property prediction: A benchmark study on open source, perovskite-like datasets
2020/10/20 by Mayr, Felix, Gagliardi, Alessio · 2 citations
#Data Analysis #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Statistics and Probability (physics.data-an)
- Simulation-based inference methods for particle physics
2020/10/13 by Brehmer, Johann, Cranmer, Kyle · 3 citations
#Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Machine Learning (stat.ML) #Statistics and Probability (physics.data-an)
- Long-timescale predictions from short-trajectory data: A benchmark analysis of the trp-cage miniprotein
2020/09/08 by Strahan, John, Antoszewski, Adam, Lorpaiboon, Chatipat +3 · 3 citations
#Biomolecules (q-bio.BM) #Computational Physics (physics.comp-ph) #Data Analysis #FOS: Biological sciences #FOS: Physical sciences #Statistics and Probability (physics.data-an)
- Deep learning for gravitational-wave data analysis: A resampling\n white-box approach
2020/09/08 by Manuel D. Morales, Morales, Manuel D., Javier M. Antelis +5 · 1 citation
Physics and Astronomy · #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (cs.LG) #Pulsars and Gravitational Waves Research #Statistics and Probability (physics.data-an)
- Estimating the parameters of ocean wave spectra
2020/08/24 by Grainger, Jake P., Sykulski, Adam M., Jonathan, Philip +1 · 2 citations
#Applications (stat.AP) #Atmospheric and Oceanic Physics (physics.ao-ph) #Computation (stat.CO) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Methodology (stat.ME) #Statistics and Probability (physics.data-an)
- Balanced k-Means Clustering on an Adiabatic Quantum Computer
2020/08/10 by Arthur, Davis, Date, Prasanna · 4 citations
#62H30 #68T05 #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #I.2.6 #Machine Learning (cs.LG) #Quantum Physics (quant-ph) #Statistics and Probability (physics.data-an)
- Bayesian Inference of Minimally Complex Models with Interactions of Arbitrary Order
2020/08/02 by Clélia de Mulatier, de Mulatier, Clélia, Matteo Marsili +1 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Data Analysis #Data Analysis with R #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Quantitative Methods (q-bio.QM) #Statistical Mechanics and Entropy #Statistical and numerical algorithms #Statistics Theory (math.ST) #Statistics and Probability (physics.data-an)
- MJOLNIR: A Software Package for Multiplexing Neutron Spectrometers
2020/07/29 by Jakob Lass, Lass, Jakob, H. Jacobsen +5 · 5 citations
Earth and Planetary Sciences · Physics and Astronomy · #Atomic and Subatomic Physics Research #Data Analysis #FOS: Physical sciences #Geological and Geophysical Studies #Materials Science (cond-mat.mtrl-sci) #Nuclear Physics and Applications #Statistics and Probability (physics.data-an)
- Objective frequentist uncertainty quantification for atmospheric CO2\n retrievals
2020/07/29 by Pratik Patil, Mikael Kuusela, Patil, Pratik +3 · 2 citations
Computer Science · Engineering · Environmental Science · #15A29 #62F30 #62P12 #90C90 #Applications (stat.AP) #Atmospheric and Environmental Gas Dynamics #Atmospheric and Oceanic Physics (physics.ao-ph) #Calibration and Measurement Techniques #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Geochemistry and Geologic Mapping #Statistics and Probability (physics.data-an)
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