Guardado en:
| Autores principales: | Menke, Hannah P., Elsheikh, Ahmed H., Wei, Lingli, Wang, Nanzhe, Busch, Andreas |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2603.14907 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Machine learning of phases and structures for model systems in physics
por: Bayo, Djenabou, et al.
Publicado: (2024)
por: Bayo, Djenabou, et al.
Publicado: (2024)
A unified theory of feature learning in RNNs and DNNs
por: Bauer, Jan P., et al.
Publicado: (2026)
por: Bauer, Jan P., et al.
Publicado: (2026)
Applying statistical learning theory to deep learning
por: Gerbelot, Cédric, et al.
Publicado: (2023)
por: Gerbelot, Cédric, et al.
Publicado: (2023)
Asymptotic theory of in-context learning by linear attention
por: Lu, Yue M., et al.
Publicado: (2024)
por: Lu, Yue M., et al.
Publicado: (2024)
High-dimensional learning of narrow neural networks
por: Cui, Hugo
Publicado: (2024)
por: Cui, Hugo
Publicado: (2024)
The effect of priors on Learning with Restricted Boltzmann Machines
por: Manzan, Gianluca, et al.
Publicado: (2024)
por: Manzan, Gianluca, et al.
Publicado: (2024)
Dynamics of Meta-learning Representation in the Teacher-student Scenario
por: Wang, Hui, et al.
Publicado: (2024)
por: Wang, Hui, et al.
Publicado: (2024)
Neural Langevin Machine: a local asymmetric learning rule can be creative
por: Yu, Zhendong, et al.
Publicado: (2025)
por: Yu, Zhendong, et al.
Publicado: (2025)
Dataset-Free Weight-Initialization on Restricted Boltzmann Machine
por: Yasuda, Muneki, et al.
Publicado: (2024)
por: Yasuda, Muneki, et al.
Publicado: (2024)
A solvable model of learning generative diffusion: theory and insights
por: Cui, Hugo, et al.
Publicado: (2025)
por: Cui, Hugo, et al.
Publicado: (2025)
Statistical physics of complex systems: glasses, spin glasses, continuous constraint satisfaction problems, high-dimensional inference and neural networks
por: Urbani, Pierfrancesco
Publicado: (2024)
por: Urbani, Pierfrancesco
Publicado: (2024)
Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions
por: Xu, Yizhou, et al.
Publicado: (2025)
por: Xu, Yizhou, et al.
Publicado: (2025)
Disordered Dynamics in High Dimensions: Connections to Random Matrices and Machine Learning
por: Bordelon, Blake, et al.
Publicado: (2026)
por: Bordelon, Blake, et al.
Publicado: (2026)
Asymptotics of feature learning in two-layer networks after one gradient-step
por: Cui, Hugo, et al.
Publicado: (2024)
por: Cui, Hugo, et al.
Publicado: (2024)
Adaptive kernel predictors from feature-learning infinite limits of neural networks
por: Lauditi, Clarissa, et al.
Publicado: (2025)
por: Lauditi, Clarissa, et al.
Publicado: (2025)
Optimal thresholds and algorithms for a model of multi-modal learning in high dimensions
por: Keup, Christian, et al.
Publicado: (2024)
por: Keup, Christian, et al.
Publicado: (2024)
Machine learning the Ising transition: A comparison between discriminative and generative approaches
por: Zhang, Difei, et al.
Publicado: (2024)
por: Zhang, Difei, et al.
Publicado: (2024)
Modeling Structured Data Learning with Restricted Boltzmann Machines in the Teacher-Student Setting
por: Thériault, Robin, et al.
Publicado: (2024)
por: Thériault, Robin, et al.
Publicado: (2024)
$L_0$ Regularization of Field-Aware Factorization Machine through Ising Model
por: Okamoto, Yasuharu
Publicado: (2024)
por: Okamoto, Yasuharu
Publicado: (2024)
Transient learning dynamics drive escape from sharp valleys in Stochastic Gradient Descent
por: Yang, Ning, et al.
Publicado: (2026)
por: Yang, Ning, et al.
Publicado: (2026)
Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks
por: D'Amico, Francesco, et al.
Publicado: (2025)
por: D'Amico, Francesco, et al.
Publicado: (2025)
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence
por: Dawid, Anna, et al.
Publicado: (2023)
por: Dawid, Anna, et al.
Publicado: (2023)
Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms
por: Demyanenko, Elizaveta, et al.
Publicado: (2025)
por: Demyanenko, Elizaveta, et al.
Publicado: (2025)
Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds
por: Troiani, Emanuele, et al.
Publicado: (2025)
por: Troiani, Emanuele, et al.
Publicado: (2025)
Isolating the hard core of phaseless inference: the Phase selection formulation
por: Straziota, Davide, et al.
Publicado: (2025)
por: Straziota, Davide, et al.
Publicado: (2025)
A solvable high-dimensional model where nonlinear autoencoders learn structure invisible to PCA while test loss misaligns with generalization
por: Mendes, Vicente Conde, et al.
Publicado: (2026)
por: Mendes, Vicente Conde, et al.
Publicado: (2026)
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
por: Duranthon, O., et al.
Publicado: (2025)
por: Duranthon, O., et al.
Publicado: (2025)
PCA recovery thresholds in low-rank matrix inference with sparse noise
por: Adomaityte, Urte, et al.
Publicado: (2025)
por: Adomaityte, Urte, et al.
Publicado: (2025)
Cell reprogramming design by transfer learning of functional transcriptional networks
por: Wytock, Thomas P., et al.
Publicado: (2024)
por: Wytock, Thomas P., et al.
Publicado: (2024)
Machine learning topological energy braiding of non-Bloch bands
por: Shi, Shuwei, et al.
Publicado: (2024)
por: Shi, Shuwei, et al.
Publicado: (2024)
Effect of imaginary gauge on wave transport in driven-dissipative systems
por: Komis, I., et al.
Publicado: (2025)
por: Komis, I., et al.
Publicado: (2025)
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems
por: Angelini, Maria Chiara, et al.
Publicado: (2023)
por: Angelini, Maria Chiara, et al.
Publicado: (2023)
Impact of heavy-tailed synaptic strength distributions on self-sustained activity in networks of spiking neurons
por: Tönjes, Ralf, et al.
Publicado: (2026)
por: Tönjes, Ralf, et al.
Publicado: (2026)
Machine-learning enabled characterization of individual ring resonators in integrated photonic lattices
por: Pereira, Elizabeth Louis, et al.
Publicado: (2026)
por: Pereira, Elizabeth Louis, et al.
Publicado: (2026)
Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models
por: Wang, Shanshan, et al.
Publicado: (2025)
por: Wang, Shanshan, et al.
Publicado: (2025)
Finite-time Lyapunov exponents of deep neural networks
por: Storm, L., et al.
Publicado: (2023)
por: Storm, L., et al.
Publicado: (2023)
Pruning-induced phases in fully-connected neural networks: the eumentia, the dementia, and the amentia
por: Pan, Haining, et al.
Publicado: (2026)
por: Pan, Haining, et al.
Publicado: (2026)
Statistical Advantage of Softmax Attention: Insights from Single-Location Regression
por: Duranthon, O., et al.
Publicado: (2025)
por: Duranthon, O., et al.
Publicado: (2025)
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model
por: Pezzicoli, F. S., et al.
Publicado: (2025)
por: Pezzicoli, F. S., et al.
Publicado: (2025)
Many-body mobility edges in one dimension revealed by efficient and interpretable feature-based learning with Kolmogorov-Arnold Networks
por: Dai, Siqi, et al.
Publicado: (2026)
por: Dai, Siqi, et al.
Publicado: (2026)
Ejemplares similares
-
Machine learning of phases and structures for model systems in physics
por: Bayo, Djenabou, et al.
Publicado: (2024) -
A unified theory of feature learning in RNNs and DNNs
por: Bauer, Jan P., et al.
Publicado: (2026) -
Applying statistical learning theory to deep learning
por: Gerbelot, Cédric, et al.
Publicado: (2023) -
Asymptotic theory of in-context learning by linear attention
por: Lu, Yue M., et al.
Publicado: (2024) -
High-dimensional learning of narrow neural networks
por: Cui, Hugo
Publicado: (2024)