Deep Neural Networks as Gaussian Processes

1 November 2017

Jascha Narain Sohl-Dickstein

UQCV

BDL

ArXiv PDF HTML

Papers citing "Deep Neural Networks as Gaussian Processes"

50 / 692 papers shown

Title
Fundamental limits of overparametrized shallow neural networks for supervised learning Francesco Camilli D. Tieplova Jean Barbier 43 9 0 11 Jul 2023
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities Guihong Li Duc-Tuong Hoang Kartikeya Bhardwaj Ming Lin Zhangyang Wang R. Marculescu 51 11 0 05 Jul 2023
Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space Zhengdao Chen 46 1 0 03 Jul 2023
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit Lorenzo Noci Chuning Li Mufan Li Bobby He Thomas Hofmann Chris J. Maddison Daniel M. Roy 46 31 0 30 Jun 2023
Introspective Perception for Mobile Robots Sadegh Rabiee Joydeep Biswas 38 3 0 29 Jun 2023
Gaussian random field approximation via Stein's method with applications to wide random neural networks Krishnakumar Balasubramanian L. Goldstein Nathan Ross Adil Salim 37 9 0 28 Jun 2023
Comparing Deep Learning Models for the Task of Volatility Prediction Using Multivariate Data Wenbo Ge Pooia Lalbakhsh Leigh Isai Artem Lenskiy Hanna Suominen OOD 23 3 0 20 Jun 2023
Representation and decomposition of functions in DAG-DNNs and structural network pruning Wonjun Hwang 30 1 0 16 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 40 0 0 10 Jun 2023
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks Ziyi Huang Henry Lam Haofeng Zhang UQCV 33 4 0 09 Jun 2023
Uniform Convergence of Deep Neural Networks with Lipschitz Continuous Activation Functions and Variable Widths Yuesheng Xu Haizhang Zhang 39 3 0 02 Jun 2023
Centered Self-Attention Layers Ameen Ali Tomer Galanti Lior Wolf 56 6 0 02 Jun 2023
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization Navid Ansari Hans-Peter Seidel Vahid Babaei 29 2 0 01 Jun 2023
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization Y. Li Tim G. J. Rudner A. Wilson BDL 42 28 0 31 May 2023
A Rainbow in Deep Network Black Boxes Florentin Guth Brice Ménard G. Rochette S. Mallat 39 10 0 29 May 2023
An Improved Variational Approximate Posterior for the Deep Wishart Process Sebastian W. Ober Ben Anson Edward Milsom Laurence Aitchison BDL 36 5 0 23 May 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 42 14 0 23 May 2023
Squared Neural Families: A New Class of Tractable Density Models Russell Tsuchida Cheng Soon Ong Dino Sejdinovic TPM 28 11 0 22 May 2023
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance Jorge Loría A. Bhadra UQCV BDL 41 1 0 18 May 2023
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks Chanwoo Chun Daniel D. Lee BDL 45 2 0 17 May 2023
A Scalable Walsh-Hadamard Regularizer to Overcome the Low-degree Spectral Bias of Neural Networks Ali Gorji Andisheh Amrollahi A. Krause 19 4 0 16 May 2023
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs Pau Batlle Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 34 17 0 08 May 2023
Structures of Neural Network Effective Theories cCaugin Ararat Tianji Cai Cem Tekin Zhengkang Zhang 60 7 0 03 May 2023
Random Function Descent Felix Benning L. Döring 26 0 0 02 May 2023
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability Sitao Luan Chenqing Hua Minkai Xu Qincheng Lu Jiaqi Zhu Xiaoming Chang Jie Fu J. Leskovec Doina Precup 46 3 0 25 Apr 2023
Generalization and Estimation Error Bounds for Model-based Neural Networks Avner Shultzman Eyar Azar M. Rodrigues Yonina C. Eldar 24 7 0 19 Apr 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization Agustinus Kristiadi Alexander Immer Runa Eschenhagen Vincent Fortuin BDL UQCV 30 8 0 17 Apr 2023
Do deep neural networks have an inbuilt Occam's razor? Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 31 16 0 13 Apr 2023
UATTA-EB: Uncertainty-Aware Test-Time Augmented Ensemble of BERTs for Classifying Common Mental Illnesses on Social Media Posts Pratinav Seth Mihir Agarwal AI4MH 23 1 0 10 Apr 2023
Non-asymptotic approximations of Gaussian neural networks via second-order Poincaré inequalities Alberto Bordino Stefano Favaro S. Fortini 28 7 0 08 Apr 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks Blake Bordelon Cengiz Pehlevan MLT 43 29 0 06 Apr 2023
Wide neural networks: From non-gaussian random fields at initialization to the NTK geometry of training Luís Carvalho Joao L. Costa José Mourao Gonccalo Oliveira AI4CE 31 1 0 06 Apr 2023
Biological Sequence Kernels with Guaranteed Flexibility Alan N. Amin Eli N. Weinstein D. Marks 40 4 0 06 Apr 2023
Self-Distillation for Gaussian Process Regression and Classification Kenneth Borup L. Andersen 21 2 0 05 Apr 2023
Effective Theory of Transformers at Initialization Emily Dinan Sho Yaida Susan Zhang 32 14 0 04 Apr 2023
VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution Jaeill Kim Suhyun Kang Duhun Hwang Jungwook Shin Wonjong Rhee DRL 18 21 0 04 Apr 2023
Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes Yifan Chen H. Owhadi F. Schafer 45 31 0 03 Apr 2023
Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting Timm Hess Eli Verwimp Gido M. van de Ven Tinne Tuytelaars CLL 33 7 0 03 Apr 2023
Neural signature kernels as infinite-width-depth-limits of controlled ResNets Nicola Muca Cirone M. Lemercier C. Salvi 26 23 0 30 Mar 2023
Inferring networks from time series: a neural approach Thomas Gaskin G. Pavliotis Mark Girolami AI4TS 32 7 0 30 Mar 2023
Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control Tyler Lekang Andrew G. Lamperski 23 0 0 28 Mar 2023
On the Stepwise Nature of Self-Supervised Learning James B. Simon Maksis Knutins Liu Ziyin Daniel Geisz Abraham J. Fetterman Joshua Albrecht SSL 42 30 0 27 Mar 2023
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle Rylan Schaeffer Mikail Khona Zachary Robertson Akhilan Boopathy Kateryna Pistunova J. Rocks Ila Rani Fiete Oluwasanmi Koyejo 72 31 0 24 Mar 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 51 0 0 24 Mar 2023
Efficient Uncertainty Estimation with Gaussian Process for Reliable Dialog Response Retrieval Tong Ye Zhitao Li Jianzong Wang Ning Cheng Jing Xiao BDL 32 1 0 15 Mar 2023
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples Ben Adlam Jaehoon Lee Shreyas Padhy Zachary Nado Jasper Snoek 26 11 0 09 Mar 2023
Bayesian inference with finitely wide neural networks Chi-Ken Lu BDL 37 0 0 06 Mar 2023
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width Dayal Singh Kalra M. Barkeshli 25 9 0 23 Feb 2023
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles Biswadeep Chakraborty Saibal Mukhopadhyay 20 10 0 22 Feb 2023
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation Bobby He James Martens Guodong Zhang Aleksandar Botev Andy Brock Samuel L. Smith Yee Whye Teh 27 30 0 20 Feb 2023