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09/01/2023
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
We propose the geometry-informed neural operator (GINO), a highly effici...
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04/26/2023
The Nonlocal Neural Operator: Universal Approximation
Neural operator architectures approximate operators between infinite-dim...
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01/19/2023
Forecasting subcritical cylinder wakes with Fourier Neural Operators
We apply Fourier neural operators (FNOs), a state-of-the-art operator le...
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11/29/2022
Fourier Continuation for Exact Derivative Computation in Physics-Informed Neural Operators
The physics-informed neural operator (PINO) is a machine learning archit...
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11/28/2022
Incremental Fourier Neural Operator
Recently, neural networks have proven their impressive ability to solve ...
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11/28/2022
Machine Learning Accelerated PDE Backstepping Observers
State estimation is important for a variety of tasks, from forecasting t...
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10/31/2022
Accelerating Carbon Capture and Storage Modeling using Fourier Neural Operators
Carbon capture and storage (CCS) is an important strategy for reducing c...
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10/28/2022
Improving Transferability of Adversarial Examples on Face Recognition with Beneficial Perturbation Feature Augmentation
Face recognition (FR) models can be easily fooled by adversarial example...
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10/27/2022
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
Lithography modeling is a crucial problem in chip design to ensure a chi...
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07/11/2022
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
Deep learning surrogate models have shown promise in solving partial dif...
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07/08/2022
Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training
Machine learning techniques have been extensively studied for mask optim...
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03/12/2022
Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks
Lithography simulation is a critical step in VLSI design and optimizatio...
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02/22/2022
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
FourCastNet, short for Fourier Forecasting Neural Network, is a global d...
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11/06/2021
Physics-Informed Neural Operator for Learning Partial Differential Equations
Machine learning methods have recently shown promise in solving partial ...
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09/03/2021
U-FNO – an enhanced Fourier neural operator based-deep learning model for multiphase flow
Numerical simulation of multiphase flow in porous media is essential for...
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08/29/2021
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution
Recent studies have shown that deep neural networks are vulnerable to in...
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08/19/2021
Neural Operator: Learning Maps Between Function Spaces
The classical development of neural networks has primarily focused on le...
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06/13/2021
Markov Neural Operators for Learning Chaotic Systems
Chaotic systems are notoriously challenging to predict because of their ...
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03/02/2021
Unsupervised Word Segmentation with Bi-directional Neural Language Model
We present an unsupervised word segmentation model, in which the learnin...
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10/18/2020
Fourier Neural Operator for Parametric Partial Differential Equations
The classical development of neural networks has primarily focused on le...
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09/16/2020
Unsupervised Summarization by Jointly Extracting Sentences and Keywords
We present RepRank, an unsupervised graph-based ranking model for extrac...
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06/16/2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations
One of the main challenges in using deep learning-based methods for simu...
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03/07/2020
Neural Operator: Graph Kernel Network for Partial Differential Equations
The classical development of neural networks has been primarily for mapp...
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06/06/2018
Conditional Linear Regression
Work in machine learning and statistics commonly focuses on building mod...
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11/13/2017