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Protopapas, Pavlos

  1. Physics-Informed Neural Networks for Quantum Eigenvalue Problems
    2022/02/24 by Henry Jin, Jin, Henry, Marios Mattheakis +3 · 8 citations
    Physics and Astronomy · Materials Science · Engineering · #Model Reduction and Neural Networks #Machine Learning in Materials Science #Power Transformer Diagnostics and Insulation
  2. One-Shot Transfer Learning of Physics-Informed Neural Networks
    2021/10/21 by Shaan Desai, Desai, Shaan, Marios Mattheakis +7 · 6 citations
    Physics and Astronomy · Computer Science · Engineering · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Nuclear Engineering Thermal-Hydraulics
  3. Unsupervised Neural Networks for Quantum Eigenvalue Problems
    2020/10/10 by Henry Jin, Jin, Henry, Marios Mattheakis +3 · 5 citations
    Computer Science · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Energy Load and Power Forecasting #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
  4. Planck and the local Universe: quantifying the tension
    2013/06/28 by Verde, Licia, Protopapas, Pavlos, Jimenez, Raul · 3 citations
    #Astrophysics of Galaxies (astro-ph.GA) #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #Solar and Stellar Astrophysics (astro-ph.SR)
  5. Gravitational Duals from Equations of State
    2024/03/21 by Yago Bea, Bea, Yago, Raúl Jiménez +11 · 6 citations
    Physics and Astronomy · #Quantum Mechanics and Applications
  6. Solving Differential Equations Using Neural Network Solution Bundles
    2020/06/17 by Flamant, Cedric, Protopapas, Pavlos, Sondak, David · 3 citations
    #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG)
  7. T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling
    2018/11/20 by Ramponi, Giorgia, Protopapas, Pavlos, Brambilla, Marco +1 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  8. Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows
    2022/11/01 by Raphaël Pellegrin, Blake Bullwinkel, Pellegrin, Raphaël +5 · 3 citations
    Computer Science · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics and Vibration Analysis #Machine Learning (cs.LG) #Model Reduction and Neural Networks
  9. FATS: Feature Analysis for Time Series
    2015/05/29 by Nun, Isadora, Protopapas, Pavlos, Sim, Brandon +4 · 1 citation
    #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM)
  10. Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks
    2022/12/14 by Olga Graf, Pablo Flores, Graf, Olga +5 · 2 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning
  11. Residual-based error bound for physics-informed neural networks
    2023/06/06 by Liu, Shuheng, Huang, Xiyue, Protopapas, Pavlos · 2 citations
    #Computational Engineering #FOS: Computer and information sciences #FOS: Mathematics #Finance #Numerical Analysis (math.NA) #and Science (cs.CE)
  12. The Denario project: Deep knowledge AI agents for scientific discovery
    2025/10/30 by Villaescusa-Navarro, Francisco, Bolliet, Boris, Villanueva-Domingo, Pablo +33 · 6 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multiagent Systems (cs.MA)
  13. One-Shot Transfer Learning for Nonlinear ODEs
    2023/11/25 by Wanzhou Lei, Lei, Wanzhou, Pavlos Protopapas +3 · 1 citation
    Engineering · Physics and Astronomy · #68T07 #FOS: Computer and information sciences #Fluid Dynamics and Turbulent Flows #I.2.1 #Machine Learning (cs.LG) #Model Reduction and Neural Networks
  14. Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems
    2022/07/03 by Liu, Shuheng, Huang, Xiyue, Protopapas, Pavlos · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Neural and Evolutionary Computing (cs.NE) #Numerical Analysis (math.NA)
  15. Efficient PINNs via Multi-Head Unimodular Regularization of the Solutions Space
    2025/01/21 by Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez, Tarancón-Álvarez, Pedro +5 · 2 citations
    Engineering · Physics and Astronomy · #Numerical methods in engineering #Model Reduction and Neural Networks #Geophysical Methods and Applications
  16. Stiff Transfer Learning for Physics-Informed Neural Networks
    2025/01/28 by Seiler, Emilien, Lei, Wanzhou, Protopapas, Pavlos · 1 citation
    #Analysis of PDEs (math.AP) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG)
  17. Deep learning for turbulent channel flow
    2018/12/05 by Rui Fang, David Sondak, Fang, Rui +5 · 1 citation
    Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Fluid Dynamics and Vibration Analysis #Fluid Dynamics and Turbulent Flows
  18. Leveraging pre-trained vision Transformers for multi-band photometric light curve classification
    2025/02/27 by Moreno-Cartagena, Daniel, Protopapas, Pavlos, Cabrera-Vives, Guillermo +3 · 1 citation
    #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM)