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में बचाया:

ग्रंथसूची विवरण
मुख्य लेखकों:	Storm, L., Linander, H., Bec, J., Gustavsson, K., Mehlig, B.
स्वरूप:	Preprint
प्रकाशित:	2023
विषय:	Disordered Systems and Neural Networks Machine Learning
ऑनलाइन पहुंच:	https://arxiv.org/abs/2306.12548
टैग:	टैग जोड़ें कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!

समान संसाधन

Emergent weight morphologies in deep neural networks
द्वारा: de Jong, Pascal, और अन्य
प्रकाशित: (2025)

Computing frustration and near-monotonicity in deep neural networks
द्वारा: Wendin, Joel, और अन्य
प्रकाशित: (2025)

Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks
द्वारा: D'Amico, Francesco, और अन्य
प्रकाशित: (2025)

Pruning-induced phases in fully-connected neural networks: the eumentia, the dementia, and the amentia
द्वारा: Pan, Haining, और अन्य
प्रकाशित: (2026)

Spring-block theory of feature learning in deep neural networks
द्वारा: Shi, Cheng, और अन्य
प्रकाशित: (2024)

New non-Euclidean neural quantum states from additional types of hyperbolic recurrent neural networks
द्वारा: Dao, H. L.
प्रकाशित: (2026)

High-dimensional learning of narrow neural networks
द्वारा: Cui, Hugo
प्रकाशित: (2024)

Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
द्वारा: Duranthon, O., और अन्य
प्रकाशित: (2025)

Deep neural networks from the perspective of ergodic theory
द्वारा: Zhang, Fan
प्रकाशित: (2023)

Supervised and Unsupervised protocols for hetero-associative neural networks
द्वारा: Alessandrelli, Andrea, और अन्य
प्रकाशित: (2025)

Towards a theory of how the structure of language is acquired by deep neural networks
द्वारा: Cagnetta, Francesco, और अन्य
प्रकाशित: (2024)

Training neural networks with structured noise improves classification and generalization
द्वारा: Benedetti, Marco, और अन्य
प्रकाशित: (2023)

Dynamic neuron approach to deep neural networks: Decoupling neurons for renormalization group analysis
द्वारा: Lee, Donghee, और अन्य
प्रकाशित: (2024)

Universal characteristics of deep neural network loss surfaces from random matrix theory
द्वारा: Baskerville, Nicholas P, और अन्य
प्रकाशित: (2022)

How does training shape the Riemannian geometry of neural network representations?
द्वारा: Zavatone-Veth, Jacob A., और अन्य
प्रकाशित: (2023)

Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation
द्वारा: Gross, Markus, और अन्य
प्रकाशित: (2023)

Boundary between noise and information applied to filtering neural network weight matrices
द्वारा: Staats, Max, और अन्य
प्रकाशित: (2022)

Adaptive kernel predictors from feature-learning infinite limits of neural networks
द्वारा: Lauditi, Clarissa, और अन्य
प्रकाशित: (2025)

Properties of the geometry of solutions and capacity of multi-layer neural networks with Rectified Linear Units activations
द्वारा: Baldassi, Carlo, और अन्य
प्रकाशित: (2019)

Solution space and storage capacity of fully connected two-layer neural networks with generic activation functions
द्वारा: Nishiyama, Sota, और अन्य
प्रकाशित: (2024)

Exact full-RSB SAT/UNSAT transition in infinitely wide two-layer neural networks
द्वारा: Annesi, Brandon L., और अन्य
प्रकाशित: (2024)

Sharp description of local minima in the loss landscape of high-dimensional two-layer ReLU neural networks
द्वारा: Huang, Jie, और अन्य
प्रकाशित: (2026)

Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds
द्वारा: Troiani, Emanuele, और अन्य
प्रकाशित: (2025)

Hyperbolic recurrent neural network as the first type of non-Euclidean neural quantum state ansatz
द्वारा: Dao, H. L.
प्रकाशित: (2025)

A simple theory for training response of deep neural networks
द्वारा: Nakazato, Kenichi
प्रकाशित: (2024)

Opening the Black Box: predicting the trainability of deep neural networks with reconstruction entropy
द्वारा: Thurn, Yanick, और अन्य
प्रकाशित: (2024)

Coding schemes in neural networks learning classification tasks
द्वारा: van Meegen, Alexander, और अन्य
प्रकाशित: (2024)

Critical feature learning in deep neural networks
द्वारा: Fischer, Kirsten, और अन्य
प्रकाशित: (2024)

Asymptotic generalization error of a single-layer graph convolutional network
द्वारा: Duranthon, O., और अन्य
प्रकाशित: (2024)

Applying statistical learning theory to deep learning
द्वारा: Gerbelot, Cédric, और अन्य
प्रकाशित: (2023)

DCEM: A deep complementary energy method for solid mechanics
द्वारा: Wang, Yizheng, और अन्य
प्रकाशित: (2023)

What can we learn from quantum convolutional neural networks?
द्वारा: Umeano, Chukwudubem, और अन्य
प्रकाशित: (2023)

On the role of non-linear latent features in bipartite generative neural networks
द्वारा: Bonnaire, Tony, और अन्य
प्रकाशित: (2025)

Improving deep neural network performance through sampling
द्वारा: Ghantasala, Lakshmi A., और अन्य
प्रकाशित: (2025)

The twin peaks of learning neural networks
द्वारा: Demyanenko, Elizaveta, और अन्य
प्रकाशित: (2024)

Online unsupervised Hebbian learning in deep photonic neuromorphic networks
द्वारा: Li, Xi, और अन्य
प्रकाशित: (2026)

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems
द्वारा: Biazzo, Indaco
प्रकाशित: (2023)

Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective
द्वारा: Ghio, Davide, और अन्य
प्रकाशित: (2023)

Divergent density of states and non-analytic Lyapunov exponent in one-dimensional slowly varying systems
द्वारा: Hu, Hai-Tao, और अन्य
प्रकाशित: (2025)

Arbitrage equilibrium and the emergence of universal microstructure in deep neural networks
द्वारा: Venkatasubramanian, Venkat, और अन्य
प्रकाशित: (2024)