Fast Adaptation with Linearized Neural Networks

2 March 2021

Papers citing "Fast Adaptation with Linearized Neural Networks"

31 / 31 papers shown

Title
SGD with memory: fundamental properties and stochastic acceleration Dmitry Yarotsky Maksim Velikanov 25 1 0 05 Oct 2024
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks Tristan Cinquin Robert Bamler UQCV BDL 38 2 0 06 Jun 2024
Dropout MPC: An Ensemble Neural MPC Approach for Systems with Learned Dynamics Spyridon Syntakas K. Vlachos 40 0 0 04 Jun 2024
Generalization error of spectral algorithms Maksim Velikanov Maxim Panov Dmitry Yarotsky 23 0 0 18 Mar 2024
Fine-tuning with Very Large Dropout Jianyu Zhang Léon Bottou 37 1 0 01 Mar 2024
The fine print on tempered posteriors Konstantinos Pitas Julyan Arbel 25 1 0 11 Sep 2023
Improving Transferability of Adversarial Examples via Bayesian Attacks Qizhang Li Yiwen Guo Xiaochen Yang W. Zuo Hao Chen AAML BDL 24 2 0 21 Jul 2023
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 16 20 0 08 Jun 2023
The Tunnel Effect: Building Data Representations in Deep Neural Networks Wojciech Masarczyk M. Ostaszewski Ehsan Imani Razvan Pascanu Piotr Milo's Tomasz Trzciñski 28 18 0 31 May 2023
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models Guillermo Ortiz-Jiménez Alessandro Favero P. Frossard MoMe 35 103 0 22 May 2023
Feature Expansion for Graph Neural Networks Jiaqi Sun Lin Zhang Guan-Hong Chen Kun Zhang Peng Xu Yujiu Yang GNN 17 13 0 10 May 2023
TRAK: Attributing Model Behavior at Scale Sung Min Park Kristian Georgiev Andrew Ilyas Guillaume Leclerc A. Madry TDI 28 127 0 24 Mar 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 21 35 0 10 Feb 2023
A Kernel-Based View of Language Model Fine-Tuning Sadhika Malladi Alexander Wettig Dingli Yu Danqi Chen Sanjeev Arora VLM 68 60 0 11 Oct 2022
Sampling-based inference for large linear models, with application to linearised Laplace Javier Antorán Shreyas Padhy Riccardo Barbano Eric T. Nalisnick David Janz José Miguel Hernández-Lobato BDL 27 17 0 10 Oct 2022
Uncertainty-Aware Meta-Learning for Multimodal Task Distributions Cesar Almecija Apoorva Sharma Navid Azizan OOD UQCV 17 3 0 04 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 24 4 0 30 Sep 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 21 5 0 22 Jun 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 25 28 0 17 Jun 2022
Few-Shot Learning by Dimensionality Reduction in Gradient Space M. Gauch M. Beck Thomas Adler D. Kotsur Stefan Fiel ... Markus Holzleitner Werner Zellinger D. Klotz Sepp Hochreiter Sebastian Lehner 33 9 0 07 Jun 2022
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv Micah Goldblum Hossein Souri Sanyam Kapoor Chen Zhu Yann LeCun A. Wilson UQCV BDL 56 43 0 20 May 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 29 314 0 06 Apr 2022
Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training? J. Mok Byunggook Na Ji-Hoon Kim Dongyoon Han Sungroh Yoon AAML 34 23 0 28 Mar 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 22 10 0 28 Feb 2022
On the adaptation of recurrent neural networks for system identification Marco Forgione Aneri Muni Dario Piga Marco Gallieri 14 17 0 21 Jan 2022
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning Utku Evci Vincent Dumoulin Hugo Larochelle Michael C. Mozer 23 83 0 10 Jan 2022
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 16 98 0 29 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 21 43 0 12 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 191 498 0 11 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 278 11,677 0 09 Mar 2017