Cover Image

Learning Dynamics of Deep Learning -- Force Analysis of Deep Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Ren, Yi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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)

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

Dynamic Latent Separation for Deep Learning
by: Tuan, Yi-Lin, et al.
Published: (2022)

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

Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
by: Fang, Ronglong, et al.
Published: (2024)

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

SoD$^2$: Statically Optimizing Dynamic Deep Neural Network
by: Niu, Wei, et al.
Published: (2024)

ManifoldFormer: Geometric Deep Learning for Neural Dynamics on Riemannian Manifolds
by: Fu, Yihang, et al.
Published: (2025)

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

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

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)

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

Increasing the Confidence of Deep Neural Networks by Coverage Analysis
by: Rossolini, Giulio, et al.
Published: (2021)

An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
by: Ke, Zhifa, et al.
Published: (2024)

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

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

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

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)

Interpretable Neural System Dynamics: Combining Deep Learning with System Dynamics Modeling to Support Critical Applications
by: D'Elia, Riccardo
Published: (2025)

The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulation
by: Deng, Huiqi, et al.
Published: (2025)

Evaluating the Dynamics of Membership Privacy in Deep Learning
by: Chen, Yuetian, et al.
Published: (2025)

Efficiency Robustness of Dynamic Deep Learning Systems
by: Rathnasuriya, Ravishka, et al.
Published: (2025)

Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning
by: Cohen, Nadav, et al.
Published: (2024)

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

Meta-Learning Loss Functions for Deep Neural Networks
by: Raymond, Christian
Published: (2024)

Bridging Computational Social Science and Deep Learning: Cultural Dissemination-Inspired Graph Neural Networks
by: Hevapathige, Asela
Published: (2025)

Enhancing Deep Learning with Optimized Gradient Descent: Bridging Numerical Methods and Neural Network Training
by: Ma, Yuhan, et al.
Published: (2024)

Does Deep Active Learning Work in the Wild?
by: Ren, Simiao, et al.
Published: (2023)

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

DeepDFA: Automata Learning through Neural Probabilistic Relaxations
by: Umili, Elena, et al.
Published: (2024)

On the Weight Dynamics of Deep Normalized Networks
by: Mehmeti-Göpel, Christian H. X. Ali, et al.
Published: (2023)

DeepAFL: Deep Analytic Federated Learning
by: Tang, Jianheng, et al.
Published: (2026)

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

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

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

A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
by: Yi, Kun, et al.
Published: (2023)

Causal Deep Learning
by: Berrevoets, Jeroen, et al.
Published: (2023)

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
by: Jiang, Jinyang, et al.
Published: (2024)