:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dunbar, John, Aaronson, Scott
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.06527
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sparsity and Out-of-Distribution Generalization
by: Aaronson, Scott, et al.
Published: (2026)

PETNet -- Coincident Particle Event Detection using Spiking Neural Networks
by: Debus, Jan, et al.
Published: (2025)

Canonical Regularisation of Wide Feature-Learning Neural Networks
by: Whittle, George, et al.
Published: (2026)

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

Why Philosophers Should Care About Computational Complexity
by: Aaronson, Scott
Published: (2011)

Toward Routing River Water in Land Surface Models with Recurrent Neural Networks
by: Lima, Mauricio, et al.
Published: (2024)

Peer-to-Peer Learning Dynamics of Wide Neural Networks
by: Chaudhari, Shreyas, et al.
Published: (2024)

Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum
by: Geifman, Amnon, et al.
Published: (2023)

Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
by: Dashtbayaz, Nima Hosseini, et al.
Published: (2024)

Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
by: Jacot, Arthur, et al.
Published: (2024)

A Simple Baseline for Stable and Plastic Neural Networks
by: Künzel, Étienne, et al.
Published: (2025)

A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
by: Calvo-Ordoñez, Sergio, et al.
Published: (2025)

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters
by: Koermer, Scott, et al.
Published: (2025)

Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks
by: Tucat, Matteo, et al.
Published: (2024)

Beyond ReLU: How Activations Affect Neural Kernels and Random Wide Networks
by: Holzmüller, David, et al.
Published: (2025)

Improving Set Function Approximation with Quasi-Arithmetic Neural Networks
by: Tokar, Tomas, et al.
Published: (2026)

Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance
by: Loría, Jorge, et al.
Published: (2023)

Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
by: Zhang, Borong, et al.
Published: (2022)

Emergence of Computational Structure in a Neural Network Physics Simulator
by: Hitchcock, Rohan, et al.
Published: (2025)

Neural Network Training with Approximate Logarithmic Computations
by: Sanyal, Arnab, et al.
Published: (2019)

Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks
by: Jin, Bangti, et al.
Published: (2025)

Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
by: Ji, Guangda, et al.
Published: (2020)

Better NTK Conditioning: A Free Lunch from (ReLU) Nonlinear Activation in Wide Neural Networks
by: Liu, Chaoyue, et al.
Published: (2023)

Random Search as a Baseline for Sparse Neural Network Architecture Search
by: Farahani, Rezsa
Published: (2024)

Reservoir Computing: A New Paradigm for Neural Networks
by: Grezes, Felix
Published: (2025)

Performing Video Frame Prediction of Microbial Growth with a Recurrent Neural Network
by: Robertson, Connor, et al.
Published: (2022)

Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
by: Jajoo, Pranaya, et al.
Published: (2026)

Network-Wide Traffic Volume Estimation from Speed Profiles using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention
by: Hein, Léo, et al.
Published: (2025)

Thermodynamics-Inspired Computing with Oscillatory Neural Networks for Inverse Matrix Computation
by: Tsormpatzoglou, George, et al.
Published: (2025)

Growing Neural Networks: Dynamic Evolution through Gradient Descent
by: Radhakrishnan, Anil, et al.
Published: (2025)

Gas Source Localization Using physics Guided Neural Networks
by: Ruiz, Victor Scott Prieto, et al.
Published: (2024)

Graph Neural Networks on Quantum Computers
by: Liao, Yidong, et al.
Published: (2024)

Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
by: Ko, Hyunouk, et al.
Published: (2024)

Accelerating Inference for Multilayer Neural Networks with Quantum Computers
by: Rattew, Arthur G., et al.
Published: (2025)

Computing Linear Regions in Neural Networks with Skip Connections
by: Joyce, Johnny, et al.
Published: (2025)

Causal Interpretation of Neural Network Computations with Contribution Decomposition
by: Melander, Joshua Brendan, et al.
Published: (2026)

Decentralized Neural Networks for Robust and Scalable Eigenvalue Computation
by: Katende, Ronald
Published: (2024)

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network
by: Jenner, Erik, et al.
Published: (2024)

Loss Spike in Training Neural Networks
by: Li, Xiaolong, et al.
Published: (2023)

Compact Bayesian Neural Networks via pruned MCMC sampling
by: Deo, Ratneel, et al.
Published: (2025)