Benjamin Peherstorfer

1. Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization
   2018/01/01 by Benjamin Peherstorfer, Karen Willcox, Max Gunzburger · 71 citations
   Decision Sciences · Computer Science · Physics and Astronomy · #Probabilistic and Robust Engineering Design #Advanced Multi-Objective Optimization Algorithms #Model Reduction and Neural Networks
2. Survey of multifidelity methods in uncertainty propagation, inference,\n and optimization
   2018/06/28 by Benjamin Peherstorfer, Karen Willcox, Peherstorfer, Benjamin +3 · 38 citations
   Decision Sciences · Computer Science · #Probabilistic and Robust Engineering Design #Advanced Multi-Objective Optimization Algorithms #Machine Learning and Data Classification
3. Optimal Model Management for Multifidelity Monte Carlo Estimation
   2016/01/01 by Benjamin Peherstorfer, Karen Willcox, Max Gunzburger · 17 citations
   Computer Science · Decision Sciences · Physics and Astronomy · #Advanced Multi-Objective Optimization Algorithms #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design
4. Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks
   2023/10/07 by Jules J. Berman, Benjamin Peherstorfer, Berman, Jules +1 · 11 citations
   Engineering · Mathematics · Physics and Astronomy · #Advanced Numerical Methods in Computational Mathematics #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical methods for differential equations
5. Manifold Approximations via Transported Subspaces: Model reduction for transport-dominated problems
   2019/12/30 by Donsub Rim, Rim, Donsub, Benjamin Peherstorfer +3 · 6 citations
   Engineering · Mathematics · Physics and Astronomy · #35F20 #41A46 #78M12 #78M34 #Computational Fluid Dynamics and Aerodynamics #FOS: Mathematics #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical methods for differential equations
6. Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates
   2015/01/01 by Benjamin Peherstorfer, Karen Willcox · 5 citations
   Engineering · Physics and Astronomy · #Computational Fluid Dynamics and Aerodynamics #Fluid Dynamics and Vibration Analysis #Model Reduction and Neural Networks
7. An Extensible Benchmark Suite for Learning to Simulate Physical Systems
   2021/08/09 by Karl Otness, Otness, Karl, Arvi Gjoka +11 · 4 citations
   Earth and Planetary Sciences · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Heat Transfer and Optimization #Machine Learning (cs.LG) #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks
8. Operator inference with roll outs for learning reduced models from scarce and low-quality data
   2022/12/02 by Wayne Isaac Tan Uy, Dirk Hartmann, Uy, Wayne Isaac Tan +3 · 5 citations
   Computer Science · Engineering · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Reservoir Engineering and Simulation Methods
9. Greedy construction of quadratic manifolds for nonlinear dimensionality reduction and nonlinear model reduction
   2024/03/11 by Paul Schwerdtner, Schwerdtner, Paul, Benjamin Peherstorfer +1 · 5 citations
   Physics and Astronomy · Engineering · Computer Science · #Model Reduction and Neural Networks #Control Systems and Identification #Advanced Vision and Imaging
10. Active operator inference for learning low-dimensional dynamical-system models from noisy data
    2021/07/20 by Wayne Isaac Tan Uy, Uy, Wayne Isaac Tan, Yuepeng Wang +5 · 2 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Neural Networks and Applications #Gaussian Processes and Bayesian Inference
11. Sequential-in-time training of nonlinear parametrizations for solving time-dependent partial differential equations
    2024/04/01 by Huan Zhang, Zhang, Huan, Yifan Chen +5 · 4 citations
    Physics and Astronomy · Engineering · #Model Reduction and Neural Networks #Advanced Measurement and Metrology Techniques
12. Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes
    2023/06/27 by Yuxiao Wen, Eric Vanden‐Eijnden, Wen, Yuxiao +3 · 3 citations
    Earth and Planetary Sciences · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Lattice Boltzmann Simulation Studies #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Seismic Imaging and Inversion Techniques
13. A transport-based multifidelity preconditioner for Markov chain Monte\n Carlo
    2018/08/28 by Benjamin Peherstorfer, Peherstorfer, Benjamin, Youssef Marzouk +1 · 1 citation
    Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Numerical Analysis (math.NA) #Probability (math.PR) #Statistical Methods and Bayesian Inference
14. CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
    2024/02/22 by Jules J. Berman, Benjamin Peherstorfer, Berman, Jules +1 · 3 citations
    Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Numerical Analysis (math.NA)
15. Operator inference of non-Markovian terms for learning reduced models\n from partially observed state trajectories
    2021/03/01 by Wayne Isaac Tan Uy, Benjamin Peherstorfer, Uy, Wayne Isaac Tan +1 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA)
16. Multi-Fidelity Covariance Estimation in the Log-Euclidean Geometry
    2023/01/31 by Aimee Maurais, Maurais, Aimee, Terrence Alsup +5 · 1 citation
    Computer Science · #Anomaly Detection Techniques and Applications #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Time Series Analysis and Forecasting
17. Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes
    2023/10/11 by Paul Schwerdtner, Schwerdtner, Paul, Philipp Schulze +5 · 1 citation
    Computer Science · Physics and Astronomy · #65M22 #65P10 #68T07 #70H33 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Neural Networks and Reservoir Computing #Numerical Analysis (math.NA)
18. Empirical sparse regression on quadratic manifolds
    2024/12/12 by Paul Schwerdtner, Serkan Gugercin, Schwerdtner, Paul +3 · 2 citations
    Computer Science · #62H25 #65F20 #65F30 #65F55 #65M22 #68T09 #Dynamical Systems (math.DS) #FOS: Mathematics #Face and Expression Recognition #Numerical Analysis (math.NA)
19. Nonlinear model reduction with Neural Galerkin schemes on quadratic manifolds
    2024/12/23 by Philipp Weder, Paul Schwerdtner, Weder, Philipp +3 · 3 citations
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Neural Networks and Applications
20. Parametric model reduction of mean-field and stochastic systems via higher-order action matching
    2024/10/15 by Jules J. Berman, Jules Berman, Berman, Jules +4 · 2 voices · 1 citation
    Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Advanced Vision and Imaging #Human Pose and Action Recognition