Nikola B. Kovachki

发表

Model Reduction and Neural Networks for Parametric PDEs pdf

Andrew M. Stuart, Bamdad Hosseini, Kaushik Bhattacharya, 2020, ArXiv.

Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning

Thomas F. Miller, Lixue Cheng, Nikola B. Kovachki, 2019, Journal of chemical theory and computation.

Analysis Of Momentum Methods pdf

Andrew M. Stuart, Nikola B. Kovachki, A. Stuart, 2019, ArXiv.

Ensemble Kalman inversion: a derivative-free technique for machine learning tasks pdf

Andrew M. Stuart, Nikola B. Kovachki, A. Stuart, 2018, Inverse Problems.

Convergence Rates for Learning Linear Operators from Noisy Data pdf

Maarten V. de Hoop, Andrew M. Stuart, Nikola B. Kovachki, 2021, ArXiv.

Continuous Time Analysis of Momentum Methods

Andrew M. Stuart, Nikola B. Kovachki, 2021, J. Mach. Learn. Res..

SMAI-JCM SMAI Journal of Computational Mathematics Model Reduction And Neural Networks For Parametric PDEs pdf

Andrew M. Stuart, Bamdad Hosseini, Kaushik Bhattacharya, 2022 .

Fourier Neural Operator for Parametric Partial Differential Equations pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Andrew Stuart, 2020, ICLR.

Neural Operator: Graph Kernel Network for Partial Differential Equations pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Andrew Stuart, 2020, ICLR 2020.

Multipole Graph Neural Operator for Parametric Partial Differential Equations pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Andrew Stuart, 2020, NeurIPS.

Convergence Rates for Learning Linear Operators from Noisy Data

Nikola B. Kovachki, Nicholas H. Nelsen, A. Stuart, 2021, ArXiv.

Learning Dissipative Dynamics in Chaotic Systems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, 2106.06898.

Neural Operator: Learning Maps Between Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Convergence Rates for Learning Linear Operators from Noisy Data

Nikola B. Kovachki, Nicholas H. Nelsen, A. Stuart, 2021, SIAM/ASA J. Uncertain. Quantification.

Fourier Neural Operator for Parametric Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2020, ICLR.

On universal approximation and error bounds for Fourier Neural Operators pdf

Siddhartha Mishra, Nikola Kovachki, Nikola B. Kovachki, 2021, J. Mach. Learn. Res..

PARAMETRIC PARTIAL DIFFERENTIAL EQUATIONS

Nikola B. Kovachki, Zongyi Li, 2020 .

Continuous Time Analysis of Momentum Methods

Nikola B. Kovachki, A. Stuart, 2019, J. Mach. Learn. Res..

Multiscale modeling of materials: Computing, data science, uncertainty and goal-oriented optimization

Nikola B. Kovachki, M. Ortiz, Burigede Liu, 2021, Mechanics of Materials.

A learning-based multiscale method and its application to inelastic impact problems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, 2102.07256.

Model Reduction and Neural Networks for Parametric PDEs

Nikola B. Kovachki, A. Stuart, K. Bhattacharya, 2020, The SMAI journal of computational mathematics.

Multipole Graph Neural Operator for Parametric Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2020, NeurIPS.

Neural Operator: Learning Maps Between Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning

Thomas F. Miller, Nikola B. Kovachki, Matthew Welborn, 2019, Journal of chemical theory and computation.

Conditional Sampling With Monotone GANs

Nikola B. Kovachki, Y. Marzouk, Bamdad Hosseini, 2020, ArXiv.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ArXiv.

Markov Neural Operators for Learning Chaotic Systems pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Kaushik Bhattacharya, 2021, ArXiv.

Score-based Diffusion Models in Function Space

Jae Hyun Lim, Vikram S. Voleti, Nikola B. Kovachki, 2023, ArXiv.

Learning Homogenization for Elliptic Operators

Nikola B. Kovachki, A. Stuart, K. Bhattacharya, 2023, ArXiv.

Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, J. Mach. Learn. Res..

Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference

Nikola B. Kovachki, Y. Marzouk, Bamdad Hosseini, 2020, 2006.06755.

Physics-Informed Neural Operator for Learning Partial Differential Equations

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2021, ACM / IMS Journal of Data Science.

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, ArXiv.

An Approximation Theory Framework for Measure-Transport Sampling Algorithms

Nikola B. Kovachki, Y. Marzouk, Bamdad Hosseini, 2023, ArXiv.

Multi-Grid Tensorized Fourier Neural Operator for High-Resolution PDEs

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, ArXiv.

Neural Operators for Accelerating Scientific Simulations and Design

Nikola B. Kovachki, Anima Anandkumar, Jean Kossaifi, 2023, ArXiv.

Geometry-Informed Neural Operator for Large-Scale 3D PDEs

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2023, NeurIPS.

Learning Chaotic Dynamics in Dissipative Systems

Nikola B. Kovachki, K. Azizzadenesheli, Anima Anandkumar, 2022, NeurIPS.

SMAI-JCM SMAI Journal of Computational Mathematics Model Reduction And Neural Networks For Parametric PDEs

Nikola B. Kovachki, A. Stuart, K. Bhattacharya, 2022 .

Conditional Sampling With Monotone GANs pdf

Bamdad Hosseini, Ricardo Baptista, Youssef Marzouk, 2020, ArXiv.

Operator Learning: Algorithms and Analysis

Nikola B. Kovachki, S. Lanthaler, Andrew M. Stuart, 2024, ArXiv.

Neural Operator: Learning Maps Between Function Spaces pdf

Kamyar Azizzadenesheli, Nikola Kovachki, Nikola B. Kovachki, 2021, arXiv.org.