Understanding the Theoretical Foundations of Deep Neural Networks through Differential Equations
Fuente:
arXiv
Saved in:
| Main Authors: | Zhao, Hongjue, Chen, Yizhuo, Wang, Yuchen, Qi, Hairong, Sha, Lui, Abdelzaher, Tarek, Shao, Huajie |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning
by: Chen, Weixin, et al.
Published: (2025)
by: Chen, Weixin, et al.
Published: (2025)
ODESteer: A Unified ODE-Based Steering Framework for LLM Alignment
by: Zhao, Hongjue, et al.
Published: (2026)
by: Zhao, Hongjue, et al.
Published: (2026)
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
by: Kimura, Tomoyoshi, et al.
Published: (2026)
by: Kimura, Tomoyoshi, et al.
Published: (2026)
SCRAG: Social Computing-Based Retrieval Augmented Generation for Community Response Forecasting in Social Media Environments
by: Sun, Dachun, et al.
Published: (2025)
by: Sun, Dachun, et al.
Published: (2025)
VISAT: Benchmarking Adversarial and Distribution Shift Robustness in Traffic Sign Recognition with Visual Attributes
by: Yu, Simon, et al.
Published: (2025)
by: Yu, Simon, et al.
Published: (2025)
Scalable Neural Symbolic Regression using Control Variables
by: Chu, Xieting, et al.
Published: (2023)
by: Chu, Xieting, et al.
Published: (2023)
Foundation Models for CPS-IoT: Opportunities and Challenges
by: Baris, Ozan, et al.
Published: (2025)
by: Baris, Ozan, et al.
Published: (2025)
A Generalizable Physics-guided Causal Model for Trajectory Prediction in Autonomous Driving
by: Zong, Zhenyu, et al.
Published: (2026)
by: Zong, Zhenyu, et al.
Published: (2026)
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
by: Cao, Hongpeng, et al.
Published: (2023)
by: Cao, Hongpeng, et al.
Published: (2023)
Deep Neural Networks Inspired by Differential Equations
by: Liu, Yongshuai, et al.
Published: (2025)
by: Liu, Yongshuai, et al.
Published: (2025)
Real-DRL: Teach and Learn in Reality
by: Mao, Yanbing, et al.
Published: (2025)
by: Mao, Yanbing, et al.
Published: (2025)
OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion
by: Wu, Yizhuo, et al.
Published: (2025)
by: Wu, Yizhuo, et al.
Published: (2025)
Neural Structure Learning with Stochastic Differential Equations
by: Wang, Benjie, et al.
Published: (2023)
by: Wang, Benjie, et al.
Published: (2023)
Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations
by: Wei, Zhao, et al.
Published: (2026)
by: Wei, Zhao, et al.
Published: (2026)
Attribution Explanations for Deep Neural Networks: A Theoretical Perspective
by: Deng, Huiqi, et al.
Published: (2025)
by: Deng, Huiqi, et al.
Published: (2025)
Information-Theoretic Foundations for Neural Scaling Laws
by: Jeon, Hong Jun, et al.
Published: (2024)
by: Jeon, Hong Jun, et al.
Published: (2024)
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations
by: Xu, Jian, et al.
Published: (2024)
by: Xu, Jian, et al.
Published: (2024)
InfoMAE: Pair-Efficient Cross-Modal Alignment for Multimodal Time-Series Sensing Signals
by: Kimura, Tomoyoshi, et al.
Published: (2025)
by: Kimura, Tomoyoshi, et al.
Published: (2025)
Fractional Differential Equation Physics-Informed Neural Network and Its Application in Battery State Estimation
by: Dang, Lujuan, et al.
Published: (2025)
by: Dang, Lujuan, et al.
Published: (2025)
Theoretical Foundations of Scaling Law in Familial Models
by: Song, Huan, et al.
Published: (2025)
by: Song, Huan, et al.
Published: (2025)
Differential Privacy Mechanisms in Neural Tangent Kernel Regression
by: Gu, Jiuxiang, et al.
Published: (2024)
by: Gu, Jiuxiang, et al.
Published: (2024)
A Theoretical Survey on Foundation Models
by: Fu, Shi, et al.
Published: (2024)
by: Fu, Shi, et al.
Published: (2024)
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
by: Xue, Kaiwen, et al.
Published: (2024)
by: Xue, Kaiwen, et al.
Published: (2024)
Social Behaviour Understanding using Deep Neural Networks: Development of Social Intelligence Systems
by: Feng, Ethan Lim Ding, et al.
Published: (2021)
by: Feng, Ethan Lim Ding, et al.
Published: (2021)
Understanding Transformer Architecture through Continuous Dynamics: A Partial Differential Equation Perspective
by: Zhang, Yukun, et al.
Published: (2024)
by: Zhang, Yukun, et al.
Published: (2024)
SENTINEL: A Multi-Level Formal Framework for Safety Evaluation of Foundation Model-based Embodied Agents
by: Zhan, Simon Sinong, et al.
Published: (2025)
by: Zhan, Simon Sinong, et al.
Published: (2025)
KGroot: Enhancing Root Cause Analysis through Knowledge Graphs and Graph Convolutional Neural Networks
by: Wang, Tingting, et al.
Published: (2024)
by: Wang, Tingting, et al.
Published: (2024)
Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks
by: Wang, Zepu, et al.
Published: (2024)
by: Wang, Zepu, et al.
Published: (2024)
HD-NDEs: Neural Differential Equations for Hallucination Detection in LLMs
by: Li, Qing, et al.
Published: (2025)
by: Li, Qing, et al.
Published: (2025)
From Neural Networks to Logical Theories: The Correspondence between Fibring Modal Logics and Fibring Neural Networks
by: Harzli, Ouns El, et al.
Published: (2025)
by: Harzli, Ouns El, et al.
Published: (2025)
Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks
by: Cichocki, Andrzej, et al.
Published: (2026)
by: Cichocki, Andrzej, et al.
Published: (2026)
Neural Laplace for learning Stochastic Differential Equations
by: Carrel, Adrien
Published: (2024)
by: Carrel, Adrien
Published: (2024)
Time and State Dependent Neural Delay Differential Equations
by: Monsel, Thibault, et al.
Published: (2023)
by: Monsel, Thibault, et al.
Published: (2023)
Towards Few-shot Self-explaining Graph Neural Networks
by: Peng, Jingyu, et al.
Published: (2024)
by: Peng, Jingyu, et al.
Published: (2024)
Physics-model-guided Worst-case Sampling for Safe Reinforcement Learning
by: Cao, Hongpeng, et al.
Published: (2024)
by: Cao, Hongpeng, et al.
Published: (2024)
KIPPO: Koopman-Inspired Proximal Policy Optimization
by: Cozma, Andrei, et al.
Published: (2025)
by: Cozma, Andrei, et al.
Published: (2025)
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks
by: Neary, Cyrus, et al.
Published: (2024)
by: Neary, Cyrus, et al.
Published: (2024)
A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments
by: Wang, Yuchen, et al.
Published: (2025)
by: Wang, Yuchen, et al.
Published: (2025)
Towards a Foundation Model for Partial Differential Equations Across Physics Domains
by: Soares, Eduardo, et al.
Published: (2025)
by: Soares, Eduardo, et al.
Published: (2025)
SPAR: Self-supervised Placement-Aware Representation Learning for Distributed Sensing
by: Chen, Yizhuo, et al.
Published: (2025)
by: Chen, Yizhuo, et al.
Published: (2025)
Similar Items
-
Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning
by: Chen, Weixin, et al.
Published: (2025) -
ODESteer: A Unified ODE-Based Steering Framework for LLM Alignment
by: Zhao, Hongjue, et al.
Published: (2026) -
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
by: Kimura, Tomoyoshi, et al.
Published: (2026) -
SCRAG: Social Computing-Based Retrieval Augmented Generation for Community Response Forecasting in Social Media Environments
by: Sun, Dachun, et al.
Published: (2025) -
VISAT: Benchmarking Adversarial and Distribution Shift Robustness in Traffic Sign Recognition with Visual Attributes
by: Yu, Simon, et al.
Published: (2025)