Gradient-based sparse voxel attacks on point cloud object detection.
Pattern Recognit., 2025
An invisible, robust copyright protection method for DNN-generated content.
Neural Networks, 2024
HeteroMorpheus: Universal Control Based on Morphological Heterogeneity Modeling.
Proceedings of the International Joint Conference on Neural Networks, 2024
PapMOT: Exploring Adversarial Patch Attack Against Multiple Object Tracking.
Proceedings of the Computer Vision - ECCV 2024, 2024
The Constrained Niching Differential Evolution Algorithm for Satellite Layout Optimization Design.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024
MorphVAE: Advancing Morphological Design of Voxel-Based Soft Robots with Variational Autoencoders.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
Bayesian physics-informed extreme learning machine for forward and inverse PDE problems with noisy data.
Neurocomputing, September, 2023
Adversarial patch attacks against aerial imagery object detectors.
Neurocomputing, June, 2023
A machine learning surrogate modeling benchmark for temperature field reconstruction of heat source systems.
Sci. China Inf. Sci., May, 2023
Natural Weather-Style Black-Box Adversarial Attacks Against Optical Aerial Detectors.
IEEE Trans. Geosci. Remote. Sens., 2023
A CNN with noise inclined module and denoise framework for hyperspectral image classification.
IET Image Process., 2023
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network.
Eng. Appl. Artif. Intell., 2023
Joint deep reversible regression model and physics-informed unsupervised learning for temperature field reconstruction.
Eng. Appl. Artif. Intell., 2023
A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications.
CoRR, 2023
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator.
CoRR, 2023
A novel meta-learning initialization method for physics-informed neural networks.
Neural Comput. Appl., 2022
Temperature field inversion of heat-source systems via physics-informed neural networks.
Eng. Appl. Artif. Intell., 2022
Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks.
CoRR, 2022
Heat Source Layout Optimization Using Automatic Deep Learning Surrogate Model and Multimodal Neighborhood Search Algorithm.
CoRR, 2022
RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks.
CoRR, 2022
Searching for Robust Neural Architectures via Comprehensive and Reliable Evaluation.
CoRR, 2022
FCA: Learning a 3D Full-Coverage Vehicle Camouflage for Multi-View Physical Adversarial Attack.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
TFRD: A Benchmark Dataset for Research on Temperature Field Reconstruction of Heat-Source Systems.
CoRR, 2021
IDRLnet: A Physics-Informed Neural Network Library.
CoRR, 2021
Physics-Informed Deep Reversible Regression Model for Temperature Field Reconstruction of Heat-Source Systems.
CoRR, 2021
A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout.
CoRR, 2021
Multisource Selective Transfer Framework in Multiobjective Optimization Problems.
IEEE Trans. Evol. Comput., 2020
Accelerating Physics-Informed Neural Network Training with Prior Dictionaries.
CoRR, 2020
A Deep Learning-Based Method for Heat Source Layout Inverse Design.
IEEE Access, 2020
Analysis of the damped nonlinear space-fractional Schrödinger equation.
Appl. Math. Comput., 2018
Stochastic symplectic and multi-symplectic methods for nonlinear Schrödinger equation with white noise dispersion.
J. Comput. Phys., 2017
Stochastic symplectic Runge-Kutta methods for the strong approximation of Hamiltonian systems with additive noise.
J. Comput. Appl. Math., 2017