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07/14/2023
RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World
Physical adversarial attacks against deep neural networks (DNNs) have re...
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07/13/2023
Multi-objective Evolutionary Search of Variable-length Composite Semantic Perturbations
Deep neural networks have proven to be vulnerable to adversarial attacks...
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05/12/2023
Efficient Search of Comprehensively Robust Neural Architectures via Multi-fidelity Evaluation
Neural architecture search (NAS) has emerged as one successful technique...
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04/20/2023
A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications
Wide deployment of deep neural networks (DNNs) based applications (e.g.,...
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04/14/2023
Multi-fidelity prediction of fluid flow and temperature field based on transfer learning using Fourier Neural Operator
Data-driven prediction of fluid flow and temperature distribution in mar...
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02/23/2023
Uncertainty Guided Ensemble Self-Training for Semi-Supervised Global Field Reconstruction
Recovering a globally accurate complex physics field from limited sensor...
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02/20/2023
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator
Perception of the full state is an essential technology to support the m...
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01/17/2023
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network
Temperature field prediction is of great importance in the thermal desig...
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12/06/2022
RBF-MGN:Solving spatiotemporal PDEs with Physics-informed Graph Neural Network
Physics-informed neural networks (PINNs) have lately received significan...
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10/19/2022
Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks
Physics-informed neural networks (PINNs) have been proposed to solve two...
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09/28/2022
A Survey on Physical Adversarial Attack in Computer Vision
In the past decade, deep learning has dramatically changed the tradition...
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09/01/2022
Physics-informed MTA-UNet: Prediction of Thermal Stress and Thermal Deformation of Satellites
The rapid analysis of thermal stress and deformation plays a pivotal rol...
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08/15/2022
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design
The phenomenon of adversarial examples has been revealed in variant scen...
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05/16/2022
Heat Source Layout Optimization Using Automatic Deep Learning Surrogate and Multimodal Neighborhood Search Algorithm
In satellite layout design, heat source layout optimization (HSLO) is an...
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05/14/2022
Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data
Physics-informed extreme learning machine (PIELM) has recently received ...
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05/02/2022
RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks
Learning solutions of partial differential equations (PDEs) with Physics...
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04/04/2022
Algorithms for Bayesian network modeling and reliability inference of complex multistate systems: Part II-Dependent systems
In using the Bayesian network (BN) to construct the complex multistate s...
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03/29/2022
Parameterized Consistency Learning-based Deep Polynomial Chaos Neural Network Method for Reliability Analysis in Aerospace Engineering
Polynomial chaos expansion (PCE) is a powerful surrogate model-based rel...
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03/15/2022
A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain
In the whole aircraft structural optimization loop, thermal analysis pla...
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03/10/2022
Semi-supervision semantic segmentation with uncertainty-guided self cross supervision
As a powerful way of realizing semi-supervised segmentation, the cross s...
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03/08/2022
Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation
Few-shot segmentation enables the model to recognize unseen classes with...
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03/07/2022
Searching for Robust Neural Architectures via Comprehensive and Reliable Evaluation
Neural architecture search (NAS) could help search for robust network ar...
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02/14/2022
Physics-Informed Deep Monte Carlo Quantile Regression method for Interval Multilevel Bayesian Network-based Satellite Heat Reliability Analysis
Temperature field reconstruction is essential for analyzing satellite he...
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02/14/2022
Deep Monte Carlo Quantile Regression for Quantifying Aleatoric Uncertainty in Physics-informed Temperature Field Reconstruction
For the temperature field reconstruction (TFR), a complex image-to-image...
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01/26/2022
A deep learning method based on patchwise training for reconstructing temperature field
Physical field reconstruction is highly desirable for the measurement an...
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01/18/2022
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks
Temperature field inversion of heat-source systems (TFI-HSS) with limite...
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09/26/2021
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
Recently, surrogate models based on deep learning have attracted much at...
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09/15/2021
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack
Physical adversarial attacks in object detection have attracted increasi...
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08/17/2021
TFRD: A Benchmark Dataset for Research on Temperature Field Reconstruction of Heat-Source Systems
Temperature field reconstruction of heat source systems (TFR-HSS) with l...
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07/23/2021
A novel meta-learning initialization method for physics-informed neural networks
Physics-informed neural networks (PINNs) have been widely used to solve ...
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07/22/2021
Mini-data-driven Deep Arbitrary Polynomial Chaos Expansion for Uncertainty Quantification
The surrogate model-based uncertainty quantification method has drawn a ...
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07/15/2021
Randomized ReLU Activation for Uncertainty Estimation of Deep Neural Networks
Deep neural networks (DNNs) have successfully learned useful data repres...
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07/09/2021
IDRLnet: A Physics-Informed Neural Network Library
Physics Informed Neural Network (PINN) is a scientific computing framewo...
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06/22/2021
Physics-Informed Deep Reversible Regression Model for Temperature Field Reconstruction of Heat-Source Systems
Temperature monitoring during the life time of heat source components in...
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03/20/2021
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout
Thermal issue is of great importance during layout design of heat source...
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04/17/2020
Accelerating Physics-Informed Neural Network Training with Prior Dictionaries
Physics-Informed Neural Networks (PINNs) can be regarded as general-purp...
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03/10/2020
Off-Road Drivable Area Extraction Using 3D LiDAR Data
We propose a method for off-road drivable area extraction using 3D LiDAR...
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09/03/2018
