:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Tangjun, Tao, Wenqi, Bao, Chenglong, Shi, Zuoqiang
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2307.12333
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Interface Laplace Learning: Learnable Interface Term Helps Semi-Supervised Learning
di: Wang, Tangjun, et al.
Pubblicazione: (2024)

Convection-Diffusion Equation: A Theoretically Certified Framework for Neural Networks
di: Wang, Tangjun, et al.
Pubblicazione: (2024)

Deep Learning with Data Privacy via Residual Perturbation
di: Tao, Wenqi, et al.
Pubblicazione: (2024)

A Nonlocal diffusion model with $H^1$ convergence for Dirichlet Boundary
di: Wang, Tangjun, et al.
Pubblicazione: (2023)

Fast and Scalable Semi-Supervised Learning for Multi-View Subspace Clustering
di: Ling, Huaming, et al.
Pubblicazione: (2024)

Reconstruction of dynamical systems from data without time labels
di: Zeng, Zhijun, et al.
Pubblicazione: (2023)

A Nonlocal $p$-Laplacian Interface Model with Sharp Interface
di: Shi, Kehan, et al.
Pubblicazione: (2026)

An invariance constrained deep learning network for PDE discovery
di: Chen, Chao, et al.
Pubblicazione: (2024)

A Nonlocal Biharmonic Model with $Γ$-Convergence to Local Model and an Efficient Numerical Method
di: Gan, Weiye, et al.
Pubblicazione: (2025)

Nonlinear functional regression by functional deep neural network with kernel embedding
di: Shi, Zhongjie, et al.
Pubblicazione: (2024)

Learning time-dependent PDE via graph neural networks and deep operator network for robust accuracy on irregular grids
di: Cho, Sung Woong, et al.
Pubblicazione: (2024)

Randomness and signal propagation in physics-informed neural networks (PINNs): A neural PDE perspective
di: Tucny, Jean-Michel, et al.
Pubblicazione: (2025)

Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint
di: Shi, Zhongjie, et al.
Pubblicazione: (2024)

Intrinsic training dynamics of deep neural networks
di: Marcotte, Sibylle, et al.
Pubblicazione: (2025)

Towards generalizable deep ptychography neural networks
di: Vong, Albert, et al.
Pubblicazione: (2025)

Explaining deep neural network models for electricity price forecasting with XAI
di: Pesenti, Antoine, et al.
Pubblicazione: (2025)

Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators
di: Gan, Weiye, et al.
Pubblicazione: (2025)

Approximation and interpolation of deep neural networks
di: Constantinescu, Vlad-Raul, et al.
Pubblicazione: (2023)

Spring-block theory of feature learning in deep neural networks
di: Shi, Cheng, et al.
Pubblicazione: (2024)

Motif distribution and function of sparse deep neural networks
di: Zahn, Olivia T., et al.
Pubblicazione: (2024)

Infinite-channel deep stable convolutional neural networks
di: Bracale, Daniele, et al.
Pubblicazione: (2021)

Accident Impact Prediction based on a deep convolutional and recurrent neural network model
di: Sajadi, Pouyan, et al.
Pubblicazione: (2024)

Efficient model predictive control for nonlinear systems modelled by deep neural networks
di: Lan, Jianglin
Pubblicazione: (2024)

RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
di: Song, Jialei, et al.
Pubblicazione: (2025)

Bayesian sparsification for deep neural networks with Bayesian model reduction
di: Marković, Dimitrije, et al.
Pubblicazione: (2023)

Hybrid deep additive neural networks
di: Kim, Gyu Min, et al.
Pubblicazione: (2024)

Implicit regularization of deep residual networks towards neural ODEs
di: Marion, Pierre, et al.
Pubblicazione: (2023)

Are classical deep neural networks weakly adversarially robust?
di: Sun, Nuolin, et al.
Pubblicazione: (2025)

An unsupervised tour through the hidden pathways of deep neural networks
di: Doimo, Diego
Pubblicazione: (2025)

Dimensionality-induced information loss of outliers in deep neural networks
di: Uematsu, Kazuki, et al.
Pubblicazione: (2024)

Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay
di: Li, Yicheng, et al.
Pubblicazione: (2024)

Flexible SE(2) graph neural networks with applications to PDE surrogates
di: Bånkestad, Maria, et al.
Pubblicazione: (2024)

On the VC dimension of deep group convolutional neural networks
di: Sepliarskaia, Anna, et al.
Pubblicazione: (2024)

Utilizing Lyapunov Exponents in designing deep neural networks
di: Mittra, Tirthankar
Pubblicazione: (2024)

Emergent weight morphologies in deep neural networks
di: de Jong, Pascal, et al.
Pubblicazione: (2025)

A least distance estimator for a multivariate regression model using deep neural networks
di: Shin, Jungmin, et al.
Pubblicazione: (2024)

Asymmetrical estimator for training encapsulated deep photonic neural networks
di: Wang, Yizhi, et al.
Pubblicazione: (2024)

Training deep physical neural networks with local physical information bottleneck
di: Wang, Hao, et al.
Pubblicazione: (2026)

Large-width functional asymptotics for deep Gaussian neural networks
di: Bracale, Daniele, et al.
Pubblicazione: (2021)

Nonlinear spiked covariance matrices and signal propagation in deep neural networks
di: Wang, Zhichao, et al.
Pubblicazione: (2024)