Cover Image

Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fang, Ronglong, Xu, Yuesheng
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Computational Advantages of Multi-Grade Deep Learning: Convergence Analysis and Performance Insights
by: Fang, Ronglong, et al.
Published: (2025)

The Spectral Bias of Shallow Neural Network Learning is Shaped by the Choice of Non-linearity
by: Sahs, Justin, et al.
Published: (2025)

Learning Dynamics of Deep Learning -- Force Analysis of Deep Neural Networks
by: Ren, Yi
Published: (2025)

Compositional Function Networks: A High-Performance Alternative to Deep Neural Networks with Built-in Interpretability
by: Li, Fang
Published: (2025)

Deep Graph Neural Point Process For Learning Temporal Interactive Networks
by: Chen, Su, et al.
Published: (2025)

Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
by: Hennig, Leona, et al.
Published: (2024)

Priors Matter: Addressing Misspecification in Bayesian Deep Q-Learning
by: van der Vaart, Pascal R., et al.
Published: (2025)

SBS: Enhancing Parameter-Efficiency of Neural Representations for Neural Networks via Spectral Bias Suppression
by: Xie, Qihu, et al.
Published: (2025)

Proximity-Informed Calibration for Deep Neural Networks
by: Xiong, Miao, et al.
Published: (2023)

Spectral Convolution on Orbifolds for Geometric Deep Learning
by: Mangliers, Tim, et al.
Published: (2026)

Layer Embedding Deep Fusion Graph Neural Network
by: Xu, Taihua, et al.
Published: (2026)

Deep Networks Learn Deep Hierarchical Models
by: Daniely, Amit
Published: (2026)

Identifying Bias in Deep Neural Networks Using Image Transforms
by: Erukude, Sai Teja, et al.
Published: (2024)

Wormhole Dynamics in Deep Neural Networks
by: Lai, Yen-Lung, et al.
Published: (2025)

The Homogeneity Trap: Spectral Collapse in Doubly-Stochastic Deep Networks
by: Liu, Yizhi
Published: (2026)

Approaching Deep Learning through the Spectral Dynamics of Weights
by: Yunis, David, et al.
Published: (2024)

Self-Abstraction Learning for Effective and Stable Training of Deep Neural Networks
by: Cho, Wonyong, et al.
Published: (2026)

Graph Neural Network contextual embedding for Deep Learning on Tabular Data
by: Villaizán-Vallelado, Mario, et al.
Published: (2023)

Addressing Bias Through Ensemble Learning and Regularized Fine-Tuning
by: Radwan, Ahmed, et al.
Published: (2024)

Eau De $Q$-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning
by: Vincent, Théo, et al.
Published: (2025)

Deep Neural Network Benchmarks for Selective Classification
by: Pugnana, Andrea, et al.
Published: (2024)

Certifying Global Robustness for Deep Neural Networks
by: Li, You, et al.
Published: (2024)

Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning
by: Wang, Longwei, et al.
Published: (2024)

BEND: Bagging Deep Learning Training Based on Efficient Neural Network Diffusion
by: Wei, Jia, et al.
Published: (2024)

On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight
by: Mustapha, Ismail B., et al.
Published: (2026)

Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks
by: Qi, Binchuan
Published: (2026)

Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
by: Ganguly, Abhisek, et al.
Published: (2026)

Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
by: Batley, Reza T., et al.
Published: (2025)

Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural Networks
by: Furlong, Aidan, et al.
Published: (2025)

Quantitative CLTs in Deep Neural Networks
by: Favaro, Stefano, et al.
Published: (2023)

Towards Scalable and Deep Graph Neural Networks via Noise Masking
by: Liang, Yuxuan, et al.
Published: (2024)

Set-Valued Sensitivity Analysis of Deep Neural Networks
by: Wang, Xin, et al.
Published: (2024)

Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks
by: Li, Xin-Chun, et al.
Published: (2024)

Enhancing Deep Neural Network Reliability with Refinement and Calibration
by: Hebbalaguppe, Ramya, et al.
Published: (2026)

Supervised Dynamic Dimension Reduction with Deep Neural Network
by: Luo, Zhanye, et al.
Published: (2025)

Decoding Generalization from Memorization in Deep Neural Networks
by: Ketha, Simran, et al.
Published: (2025)

Compressing Deep Neural Networks Using Explainable AI
by: Soroush, Kimia, et al.
Published: (2025)

Deep Manifold Part 2: Neural Network Mathematics
by: Ma, Max Y., et al.
Published: (2025)

Hierarchical Zero-Order Optimization for Deep Neural Networks
by: Cao, Sansheng, et al.
Published: (2026)

Human-like Forgetting Curves in Deep Neural Networks
by: Kline, Dylan
Published: (2025)