Epistemic Uncertainty and Observation Noise with the Neural Tangent Kernel
Fuente:
arXiv
Saved in:
| Main Authors: | Calvo-Ordoñez, Sergio, Palla, Konstantina, Ciosek, Kamil |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Neural Tangent Kernel for Classification
by: Plenk, Jonathan, et al.
Published: (2026)
by: Plenk, Jonathan, et al.
Published: (2026)
A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
by: Calvo-Ordoñez, Sergio, et al.
Published: (2025)
by: Calvo-Ordoñez, Sergio, et al.
Published: (2025)
Fast Adversarial Attacks with Gradient Prediction
by: Ciosek, Kamil, et al.
Published: (2026)
by: Ciosek, Kamil, et al.
Published: (2026)
Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025)
by: Wilson, Joseph, et al.
Published: (2025)
On the Importance of Uncertainty in Decision-Making with Large Language Models
by: Felicioni, Nicolò, et al.
Published: (2024)
by: Felicioni, Nicolò, et al.
Published: (2024)
Equivariant Neural Tangent Kernels
by: Misof, Philipp, et al.
Published: (2024)
by: Misof, Philipp, et al.
Published: (2024)
Richer Bayesian Last Layers with Subsampled NTK Features
by: Calvo-Ordoñez, Sergio, et al.
Published: (2026)
by: Calvo-Ordoñez, Sergio, et al.
Published: (2026)
Hallucination Detection on a Budget: Efficient Bayesian Estimation of Semantic Entropy
by: Ciosek, Kamil, et al.
Published: (2025)
by: Ciosek, Kamil, et al.
Published: (2025)
A Bayesian Information-Theoretic Approach to Data Attribution
by: Tailor, Dharmesh, et al.
Published: (2026)
by: Tailor, Dharmesh, et al.
Published: (2026)
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation
by: Yang, Yilin, et al.
Published: (2023)
by: Yang, Yilin, et al.
Published: (2023)
Linear Gradient Prediction with Control Variates
by: Ciosek, Kamil, et al.
Published: (2025)
by: Ciosek, Kamil, et al.
Published: (2025)
Issues with Neural Tangent Kernel Approach to Neural Networks
by: Liu, Haoran, et al.
Published: (2025)
by: Liu, Haoran, et al.
Published: (2025)
Efficient Analysis of the Distilled Neural Tangent Kernel
by: Mahowald, Jamie, et al.
Published: (2026)
by: Mahowald, Jamie, et al.
Published: (2026)
Topological Neural Tangent Kernel
by: Krishnagopal, Sanjukta
Published: (2026)
by: Krishnagopal, Sanjukta
Published: (2026)
The Minimax Rate of Second-Order Calibration
by: Ciosek, Kamil, et al.
Published: (2026)
by: Ciosek, Kamil, et al.
Published: (2026)
An Application of the Holonomic Gradient Method to the Neural Tangent Kernel
by: Sakoda, Akihiro, et al.
Published: (2024)
by: Sakoda, Akihiro, et al.
Published: (2024)
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
by: Chen, Guhan, et al.
Published: (2024)
by: Chen, Guhan, et al.
Published: (2024)
Understanding the Evolution of the Neural Tangent Kernel at the Edge of Stability
by: Jiang, Kaiqi, et al.
Published: (2025)
by: Jiang, Kaiqi, et al.
Published: (2025)
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators
by: Gan, Weiye, et al.
Published: (2025)
by: Gan, Weiye, et al.
Published: (2025)
Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
by: Benigni, Lucas, et al.
Published: (2025)
by: Benigni, Lucas, et al.
Published: (2025)
Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Divergence of Empirical Neural Tangent Kernel in Classification Problems
by: Yu, Zixiong, et al.
Published: (2025)
by: Yu, Zixiong, et al.
Published: (2025)
The Positivity of the Neural Tangent Kernel
by: Carvalho, Luís, et al.
Published: (2024)
by: Carvalho, Luís, et al.
Published: (2024)
DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
by: Dupuis, Benjamin, et al.
Published: (2021)
by: Dupuis, Benjamin, et al.
Published: (2021)
Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
by: Engel, Andrew, et al.
Published: (2023)
by: Engel, Andrew, et al.
Published: (2023)
Fast Graph Condensation with Structure-based Neural Tangent Kernel
by: Wang, Lin, et al.
Published: (2023)
by: Wang, Lin, et al.
Published: (2023)
Differential Privacy Mechanisms in Neural Tangent Kernel Regression
by: Gu, Jiuxiang, et al.
Published: (2024)
by: Gu, Jiuxiang, et al.
Published: (2024)
Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs
by: Varga-Umbrich, Eszter, et al.
Published: (2026)
by: Varga-Umbrich, Eszter, et al.
Published: (2026)
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
by: Bergna, Richard, et al.
Published: (2024)
by: Bergna, Richard, et al.
Published: (2024)
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
by: Gu, Lingyu, et al.
Published: (2024)
by: Gu, Lingyu, et al.
Published: (2024)
Measuring Uncertainty Calibration
by: Ciosek, Kamil, et al.
Published: (2025)
by: Ciosek, Kamil, et al.
Published: (2025)
Finite-Width Neural Tangent Kernels from Feynman Diagrams
by: Guillen, Max, et al.
Published: (2025)
by: Guillen, Max, et al.
Published: (2025)
On the Convergence Analysis of Over-Parameterized Variational Autoencoders: A Neural Tangent Kernel Perspective
by: Wang, Li, et al.
Published: (2024)
by: Wang, Li, et al.
Published: (2024)
Model Evolution Under Zeroth-Order Optimization: A Neural Tangent Kernel Perspective
by: Zhang, Chen, et al.
Published: (2026)
by: Zhang, Chen, et al.
Published: (2026)
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
by: Zhang, Haobo, et al.
Published: (2024)
by: Zhang, Haobo, et al.
Published: (2024)
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
by: Incudini, Massimiliano, et al.
Published: (2022)
by: Incudini, Massimiliano, et al.
Published: (2022)
Model Reprogramming Demystified: A Neural Tangent Kernel Perspective
by: Chung, Ming-Yu, et al.
Published: (2025)
by: Chung, Ming-Yu, et al.
Published: (2025)
Nonlocal Neural Tangent Kernels via Parameter-Space Interactions
by: Nagaraj, Sriram, et al.
Published: (2025)
by: Nagaraj, Sriram, et al.
Published: (2025)
The Epistemic Uncertainty Hole: an issue of Bayesian Neural Networks
by: Fellaji, Mohammed, et al.
Published: (2024)
by: Fellaji, Mohammed, et al.
Published: (2024)
Energy-based Epistemic Uncertainty for Graph Neural Networks
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
Similar Items
-
The Neural Tangent Kernel for Classification
by: Plenk, Jonathan, et al.
Published: (2026) -
A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
by: Calvo-Ordoñez, Sergio, et al.
Published: (2025) -
Fast Adversarial Attacks with Gradient Prediction
by: Ciosek, Kamil, et al.
Published: (2026) -
Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025) -
On the Importance of Uncertainty in Decision-Making with Large Language Models
by: Felicioni, Nicolò, et al.
Published: (2024)