Cover Image

Infinite-channel deep stable convolutional neural networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bracale, Daniele, Favaro, Stefano, Fortini, Sandra, Peluchetti, Stefano
Format:	Preprint
Published:	2021
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large-width functional asymptotics for deep Gaussian neural networks
by: Bracale, Daniele, et al.
Published: (2021)

Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities
by: Bordino, Alberto, et al.
Published: (2023)

Quasi-Bayesian sequential deconvolution
by: Favaro, Stefano, et al.
Published: (2024)

Quasi-Bayes empirical Bayes: a sequential approach to the Poisson compound decision problem
by: Favaro, Stefano, et al.
Published: (2024)

Function-Space MCMC for Bayesian Wide Neural Networks
by: Pezzetti, Lucia, et al.
Published: (2024)

BM$^2$: Coupled Schrödinger Bridge Matching
by: Peluchetti, Stefano
Published: (2024)

KamonBench: A Grammar-Based Dataset for Evaluating Compositional Factor Recovery in Vision-Language Models
by: Sproat, Richard, et al.
Published: (2026)

Student-t processes as infinite-width limits of posterior Bayesian neural networks
by: Caporali, Francesco, et al.
Published: (2025)

Binomial flows: Denoising and flow matching for discrete ordinal data
by: Shenfeld, Yair, et al.
Published: (2026)

HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations
by: Angioletti, Daniele, et al.
Published: (2024)

On the VC dimension of deep group convolutional neural networks
by: Sepliarskaia, Anna, et al.
Published: (2024)

The role of data embedding in equivariant quantum convolutional neural networks
by: Das, Sreetama, et al.
Published: (2023)

Latent-Augmented Discrete Diffusion Models
by: Shariatian, Dario, et al.
Published: (2025)

Symplectic convolutional neural networks
by: Yıldız, Süleyman, et al.
Published: (2025)

Multi-channel convolutional neural quantum embedding
by: Kim, Yujin, et al.
Published: (2025)

Accident Impact Prediction based on a deep convolutional and recurrent neural network model
by: Sajadi, Pouyan, et al.
Published: (2024)

Elements of Conformal Prediction for Statisticians
by: Sesia, Matteo, et al.
Published: (2026)

Theory of periodic convolutional neural network
by: Liu, Yuqing
Published: (2025)

Spectral complexity of deep neural networks
by: Di Lillo, Simmaco, et al.
Published: (2024)

DeepCFD: Efficient near-ground airfoil lift coefficient approximation with deep convolutional neural networks
by: Esabat, Mohammad Amin, et al.
Published: (2025)

Large-scale entity resolution via microclustering Ewens--Pitman random partitions
by: Beraha, Mario, et al.
Published: (2025)

Prediction of flow and elastic stresses in a viscoelastic turbulent channel flow using convolutional neural networks
by: Balasubramanian, Arivazhagan G., et al.
Published: (2024)

Metalearning traffic assignment for network disruptions with graph convolutional neural networks
by: Agriesti, Serio, et al.
Published: (2026)

On the rates of convergence for learning with convolutional neural networks
by: Yang, Yunfei, et al.
Published: (2024)

Learning the Distribution Map in Reverse Causal Performative Prediction
by: Bracale, Daniele, et al.
Published: (2024)

Sparser, Faster, Lighter Transformer Language Models
by: Cetin, Edoardo, et al.
Published: (2026)

ConvConcatNet: a deep convolutional neural network to reconstruct mel spectrogram from the EEG
by: Xu, Xiran, et al.
Published: (2024)

Large deviation principles for convolutional Bayesian neural networks
by: Bassetti, Federico, et al.
Published: (2026)

Power side-channel leakage localization through adversarial training of deep neural networks
by: Gammell, Jimmy, et al.
Published: (2024)

Imaging at the quantum limit with convolutional neural networks
by: Proppe, Andrew H., et al.
Published: (2025)

Making deep neural networks right for the right scientific reasons by interacting with their explanations
by: Schramowski, Patrick, et al.
Published: (2020)

Convergence of gradient flow for learning convolutional neural networks
by: Diederen, Jona-Maria, et al.
Published: (2026)

Resource-efficient equivariant quantum convolutional neural networks
by: Chinzei, Koki, et al.
Published: (2024)

Learning velocity model for complex media with deep convolutional neural networks
by: Stankevich, A., et al.
Published: (2021)

Learning local discrete features in explainable-by-design convolutional neural networks
by: Kaplanoglou, Pantelis I., et al.
Published: (2024)

Gaussian credible intervals in Bayesian nonparametric estimation of the unseen
by: Contardi, Claudia, et al.
Published: (2025)

Discovering influential text using convolutional neural networks
by: Ayers, Megan, et al.
Published: (2024)

sHGCN: Simplified hyperbolic graph convolutional neural networks
by: Arévalo, Pol, et al.
Published: (2025)

Revenue Maximization Under Sequential Price Competition Via The Estimation Of s-Concave Demand Functions
by: Bracale, Daniele, et al.
Published: (2025)

One-step learning algorithm selection for classification via convolutional neural networks
by: Maldonado, Sebastian, et al.
Published: (2023)