A Spin Glass Characterization of Neural Networks
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Li, Jun |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Demolition and Reinforcement of Memories in Spin-Glass-like Neural Networks
par: Ventura, Enrico
Publié: (2024)
par: Ventura, Enrico
Publié: (2024)
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics
par: Avidan, Yehonatan, et autres
Publié: (2023)
par: Avidan, Yehonatan, et autres
Publié: (2023)
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime
par: Defilippis, Leonardo, et autres
Publié: (2025)
par: Defilippis, Leonardo, et autres
Publié: (2025)
Approximation Theory for Neural Networks: Old and New
par: Mukherjee, Soumendu Sundar, et autres
Publié: (2026)
par: Mukherjee, Soumendu Sundar, et autres
Publié: (2026)
Predictive Coding Graphs are a Superset of Feedforward Neural Networks
par: van Zwol, Björn
Publié: (2026)
par: van Zwol, Björn
Publié: (2026)
Exploring Loss Landscapes through the Lens of Spin Glass Theory
par: Liao, Hao, et autres
Publié: (2024)
par: Liao, Hao, et autres
Publié: (2024)
Towards Distributed Neural Architectures
par: Cowsik, Aditya, et autres
Publié: (2025)
par: Cowsik, Aditya, et autres
Publié: (2025)
KAN: Kolmogorov-Arnold Networks
par: Liu, Ziming, et autres
Publié: (2024)
par: Liu, Ziming, et autres
Publié: (2024)
Graph Learning Metallic Glass Discovery from Wikipedia
par: Ouyang, K. -C., et autres
Publié: (2025)
par: Ouyang, K. -C., et autres
Publié: (2025)
Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer
par: Lauditi, Clarissa, et autres
Publié: (2026)
par: Lauditi, Clarissa, et autres
Publié: (2026)
Learning About Learning: A Physics Path from Spin Glasses to Artificial Intelligence
par: Caprioti, Denis D., et autres
Publié: (2026)
par: Caprioti, Denis D., et autres
Publié: (2026)
Spectral Architecture Search for Neural Network Models
par: Peri, Gianluca, et autres
Publié: (2025)
par: Peri, Gianluca, et autres
Publié: (2025)
Neural Networks as Spin Models: From Glass to Hidden Order Through Training
par: Barney, Richard, et autres
Publié: (2024)
par: Barney, Richard, et autres
Publié: (2024)
Entropic Confinement and Mode Connectivity in Overparameterized Neural Networks
par: Di Carlo, Luca, et autres
Publié: (2025)
par: Di Carlo, Luca, et autres
Publié: (2025)
Advantage of Quantum Neural Networks as Quantum Information Decoders
par: Zhong, Weishun, et autres
Publié: (2024)
par: Zhong, Weishun, et autres
Publié: (2024)
Statistical Mechanics and Artificial Neural Networks: Principles, Models, and Applications
par: Böttcher, Lucas, et autres
Publié: (2024)
par: Böttcher, Lucas, et autres
Publié: (2024)
Predictive Coding Networks and Inference Learning: Tutorial and Survey
par: van Zwol, Björn, et autres
Publié: (2024)
par: van Zwol, Björn, et autres
Publié: (2024)
A Geometric Perspective on the Difficulties of Learning GNN-based SAT Solvers
par: Skenderi, Geri
Publié: (2025)
par: Skenderi, Geri
Publié: (2025)
A Scalable Measure of Loss Landscape Curvature for Analyzing the Training Dynamics of LLMs
par: Kalra, Dayal Singh, et autres
Publié: (2026)
par: Kalra, Dayal Singh, et autres
Publié: (2026)
A method for quantifying the generalization capabilities of generative models for solving Ising models
par: Ma, Qunlong, et autres
Publié: (2024)
par: Ma, Qunlong, et autres
Publié: (2024)
Estimating Global Input Relevance and Enforcing Sparse Representations with a Scalable Spectral Neural Network Approach
par: Chicchi, Lorenzo, et autres
Publié: (2024)
par: Chicchi, Lorenzo, et autres
Publié: (2024)
Generalization through variance: how noise shapes inductive biases in diffusion models
par: Vastola, John J.
Publié: (2025)
par: Vastola, John J.
Publié: (2025)
Identifying internal patterns in (1+1)-dimensional directed percolation using neural networks
par: Parkhomenko, Danil, et autres
Publié: (2025)
par: Parkhomenko, Danil, et autres
Publié: (2025)
Grokking vs. Learning: Same Features, Different Encodings
par: Manning-Coe, Dmitry, et autres
Publié: (2025)
par: Manning-Coe, Dmitry, et autres
Publié: (2025)
Applications of Statistical Field Theory in Deep Learning
par: Ringel, Zohar, et autres
Publié: (2025)
par: Ringel, Zohar, et autres
Publié: (2025)
Representation Learning on a Random Lattice
par: Brill, Aryeh
Publié: (2025)
par: Brill, Aryeh
Publié: (2025)
Parameter Symmetry Potentially Unifies Deep Learning Theory
par: Ziyin, Liu, et autres
Publié: (2025)
par: Ziyin, Liu, et autres
Publié: (2025)
Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate
par: Kalra, Dayal Singh, et autres
Publié: (2026)
par: Kalra, Dayal Singh, et autres
Publié: (2026)
How Do Transformers "Do" Physics? Investigating the Simple Harmonic Oscillator
par: Kantamneni, Subhash, et autres
Publié: (2024)
par: Kantamneni, Subhash, et autres
Publié: (2024)
On the origin of neural scaling laws: from random graphs to natural language
par: Barkeshli, Maissam, et autres
Publié: (2026)
par: Barkeshli, Maissam, et autres
Publié: (2026)
The Persian Rug: solving toy models of superposition using large-scale symmetries
par: Cowsik, Aditya, et autres
Publié: (2024)
par: Cowsik, Aditya, et autres
Publié: (2024)
Learning Shrinks the Hard Tail: Training-Dependent Inference Scaling in a Solvable Linear Model
par: Levi, Noam
Publié: (2026)
par: Levi, Noam
Publié: (2026)
More Bang for the Buck: Improving the Inference of Large Language Models at a Fixed Budget using Reset and Discard (ReD)
par: Meir, Sagi, et autres
Publié: (2026)
par: Meir, Sagi, et autres
Publié: (2026)
Enhancing Noise-Robust Losses for Large-Scale Noisy Data Learning
par: Staats, Max, et autres
Publié: (2023)
par: Staats, Max, et autres
Publié: (2023)
Smooth Kolmogorov Arnold networks enabling structural knowledge representation
par: Samadi, Moein E., et autres
Publié: (2024)
par: Samadi, Moein E., et autres
Publié: (2024)
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
par: Li, Haoyu, et autres
Publié: (2023)
par: Li, Haoyu, et autres
Publié: (2023)
Grokking as Dimensional Phase Transition in Neural Networks
par: Wang, Ping
Publié: (2026)
par: Wang, Ping
Publié: (2026)
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
par: Colombo, Luca, et autres
Publié: (2025)
par: Colombo, Luca, et autres
Publié: (2025)
Is Grokking a Computational Glass Relaxation?
par: Zhang, Xiaotian, et autres
Publié: (2025)
par: Zhang, Xiaotian, et autres
Publié: (2025)
Preisach Attention: A Hysteretic Model of Sequential Memory
par: Frydrych, Piotr
Publié: (2026)
par: Frydrych, Piotr
Publié: (2026)
Documents similaires
-
Demolition and Reinforcement of Memories in Spin-Glass-like Neural Networks
par: Ventura, Enrico
Publié: (2024) -
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics
par: Avidan, Yehonatan, et autres
Publié: (2023) -
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime
par: Defilippis, Leonardo, et autres
Publié: (2025) -
Approximation Theory for Neural Networks: Old and New
par: Mukherjee, Soumendu Sundar, et autres
Publié: (2026) -
Predictive Coding Graphs are a Superset of Feedforward Neural Networks
par: van Zwol, Björn
Publié: (2026)