Convolutional Deep Kernel Machines
Fuente:
arXiv
Saved in:
| Main Authors: | Milsom, Edward, Anson, Ben, Aitchison, Laurence |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
by: Milsom, Edward, et al.
Published: (2024)
by: Milsom, Edward, et al.
Published: (2024)
Flexible Infinite-Width Graph Convolutional Neural Networks
by: Anson, Ben, et al.
Published: (2024)
by: Anson, Ben, et al.
Published: (2024)
Function-Space Learning Rates
by: Milsom, Edward, et al.
Published: (2025)
by: Milsom, Edward, et al.
Published: (2025)
Controlling changes to attention logits
by: Anson, Ben, et al.
Published: (2025)
by: Anson, Ben, et al.
Published: (2025)
Scale-invariant Attention
by: Anson, Ben, et al.
Published: (2025)
by: Anson, Ben, et al.
Published: (2025)
Why you don't overfit, and don't need Bayes if you only train for one epoch
by: Aitchison, Laurence
Published: (2024)
by: Aitchison, Laurence
Published: (2024)
Batch size invariant Adam
by: Wang, Xi, et al.
Published: (2024)
by: Wang, Xi, et al.
Published: (2024)
How to set AdamW's weight decay as you scale model and dataset size
by: Wang, Xi, et al.
Published: (2024)
by: Wang, Xi, et al.
Published: (2024)
Learning to Skip the Middle Layers of Transformers
by: Lawson, Tim, et al.
Published: (2025)
by: Lawson, Tim, et al.
Published: (2025)
Using Neural Networks for Data Cleaning in Weather Datasets
by: Hanslope, Jack R. P., et al.
Published: (2024)
by: Hanslope, Jack R. P., et al.
Published: (2024)
Massively Parallel Expectation Maximization For Approximate Posteriors
by: Heap, Thomas, et al.
Published: (2025)
by: Heap, Thomas, et al.
Published: (2025)
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
by: Yang, Adam X., et al.
Published: (2023)
by: Yang, Adam X., et al.
Published: (2023)
Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers
by: Heap, Thomas, et al.
Published: (2025)
by: Heap, Thomas, et al.
Published: (2025)
Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
by: Bowyer, Sam, et al.
Published: (2025)
by: Bowyer, Sam, et al.
Published: (2025)
Bayesian Low-rank Adaptation for Large Language Models
by: Yang, Adam X., et al.
Published: (2023)
by: Yang, Adam X., et al.
Published: (2023)
Residual Stream Analysis with Multi-Layer SAEs
by: Lawson, Tim, et al.
Published: (2024)
by: Lawson, Tim, et al.
Published: (2024)
Inverse-Free Sparse Variational Gaussian Processes
by: Cortinovis, Stefano, et al.
Published: (2026)
by: Cortinovis, Stefano, et al.
Published: (2026)
Machine learning emulation of precipitation from km-scale UK regional climate simulations using a diffusion model
by: Addison, Henry, et al.
Published: (2024)
by: Addison, Henry, et al.
Published: (2024)
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
by: Farnik, Lucy, et al.
Published: (2025)
by: Farnik, Lucy, et al.
Published: (2025)
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
by: Lee, Meng-Chieh, et al.
Published: (2024)
by: Lee, Meng-Chieh, et al.
Published: (2024)
Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference
by: Fox, David, et al.
Published: (2026)
by: Fox, David, et al.
Published: (2026)
Kernel Normalized Convolutional Networks
by: Nasirigerdeh, Reza, et al.
Published: (2022)
by: Nasirigerdeh, Reza, et al.
Published: (2022)
Questionable practices in machine learning
by: Leech, Gavin, et al.
Published: (2024)
by: Leech, Gavin, et al.
Published: (2024)
Unified Kernel-Segregated Transpose Convolution Operation
by: Tida, Vijay Srinivas, et al.
Published: (2025)
by: Tida, Vijay Srinivas, et al.
Published: (2025)
Correlating Time Series with Interpretable Convolutional Kernels
by: Chen, Xinyu, et al.
Published: (2024)
by: Chen, Xinyu, et al.
Published: (2024)
Learning to Approximate Adaptive Kernel Convolution on Graphs
by: Sim, Jaeyoon, et al.
Published: (2024)
by: Sim, Jaeyoon, et al.
Published: (2024)
CKGConv: General Graph Convolution with Continuous Kernels
by: Ma, Liheng, et al.
Published: (2024)
by: Ma, Liheng, 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)
Spatio-Temporal Graph Convolutional Networks: Optimised Temporal Architecture
by: Turner, Edward
Published: (2025)
by: Turner, Edward
Published: (2025)
Bayesian Reward Models for LLM Alignment
by: Yang, Adam X., et al.
Published: (2024)
by: Yang, Adam X., et al.
Published: (2024)
Deep Kernel Fusion for Transformers
by: Zhang, Zixi, et al.
Published: (2026)
by: Zhang, Zixi, et al.
Published: (2026)
On the Nystrom Approximation for Preconditioning in Kernel Machines
by: Abedsoltan, Amirhesam, et al.
Published: (2023)
by: Abedsoltan, Amirhesam, et al.
Published: (2023)
Notes on Kernel Methods in Machine Learning
by: Pérez-Rosero, Diego Armando, et al.
Published: (2025)
by: Pérez-Rosero, Diego Armando, et al.
Published: (2025)
One Class Restricted Kernel Machines
by: Quadir, A., et al.
Published: (2025)
by: Quadir, A., et al.
Published: (2025)
Multiple Locally Linear Kernel Machines
by: Picard, David
Published: (2024)
by: Picard, David
Published: (2024)
Deep Hierarchical Graph Alignment Kernels
by: Tang, Shuhao, et al.
Published: (2024)
by: Tang, Shuhao, et al.
Published: (2024)
Analysis of Structured Deep Kernel Networks
by: Wenzel, Tizian, et al.
Published: (2021)
by: Wenzel, Tizian, et al.
Published: (2021)
Twin Restricted Kernel Machines for Multiview Classification
by: Quadir, A., et al.
Published: (2025)
by: Quadir, A., et al.
Published: (2025)
Spectral Truncation Kernels: Noncommutativity in $C^*$-algebraic Kernel Machines
by: Hashimoto, Yuka, et al.
Published: (2024)
by: Hashimoto, Yuka, et al.
Published: (2024)
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
by: Ben-Yair, Ido, et al.
Published: (2021)
by: Ben-Yair, Ido, et al.
Published: (2021)
Similar Items
-
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
by: Milsom, Edward, et al.
Published: (2024) -
Flexible Infinite-Width Graph Convolutional Neural Networks
by: Anson, Ben, et al.
Published: (2024) -
Function-Space Learning Rates
by: Milsom, Edward, et al.
Published: (2025) -
Controlling changes to attention logits
by: Anson, Ben, et al.
Published: (2025) -
Scale-invariant Attention
by: Anson, Ben, et al.
Published: (2025)