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Deep Neural Networks as Gaussian Processes

1 November 2017

Jascha Narain Sohl-Dickstein

UQCV

BDL

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Papers citing "Deep Neural Networks as Gaussian Processes"

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Title
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines Edward Milsom Ben Anson Laurence Aitchison 65 0 0 08 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 143 0 0 08 Oct 2024
Strong Model Collapse Elvis Dohmatob Yunzhen Feng Arjun Subramonian Julia Kempe 92 15 0 07 Oct 2024
Deep Kernel Posterior Learning under Infinite Variance Prior Weights Jorge Loría A. Bhadra BDL UQCV 161 0 0 02 Oct 2024
Functional Stochastic Gradient MCMC for Bayesian Neural Networks Mengjing Wu Junyu Xuan Jie Lu BDL 86 0 0 25 Sep 2024
BGDB: Bernoulli-Gaussian Decision Block with Improved Denoising Diffusion Probabilistic Models Chengkun Sun Jinqian Pan Russell Stevens Terry Jiang Bian Jie Xu DiffM 65 1 0 19 Sep 2024
Rate-Constrained Quantization for Communication-Efficient Federated Learning Shayan Mohajer Hamidi Ali Bereyhi FedML MQ 60 1 0 10 Sep 2024
NASH: Neural Architecture and Accelerator Search for Multiplication-Reduced Hybrid Models Yang Xu Huihong Shi Zhongfeng Wang 85 0 0 07 Sep 2024
Function-Space MCMC for Bayesian Wide Neural Networks Lucia Pezzetti Stefano Favaro Stefano Peluchetti BDL 469 0 0 26 Aug 2024
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks Shrenik Zinage Sudeepta Mondal S. Sarkar 112 7 0 30 Jul 2024
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection Steven Adams A. Patané Morteza Lahijanian Luca Laurenti BDL 98 3 0 26 Jul 2024
Gaussian Process Kolmogorov-Arnold Networks Andrew Siyuan Chen 71 0 0 25 Jul 2024
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective Jingren Liu Zhong Ji YunLong Yu Jiale Cao Yanwei Pang Jungong Han Xuelong Li CLL 152 5 0 24 Jul 2024
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing Biswadeep Chakraborty Saibal Mukhopadhyay 99 2 0 08 Jul 2024
Neural varifolds: an aggregate representation for quantifying the geometry of point clouds Juheon Lee Xiaohao Cai Carola-Bibian Schönlieb Simon Masnou 3DPC 93 1 0 05 Jul 2024
Coding schemes in neural networks learning classification tasks Alexander van Meegen H. Sompolinsky 98 10 0 24 Jun 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 225 0 0 10 Jun 2024
Crafting Heavy-Tails in Weight Matrix Spectrum without Gradient Noise Vignesh Kothapalli Tianyu Pang Shenyang Deng Zongmin Liu Yaoqing Yang 92 4 0 07 Jun 2024
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation Tian Zeng Junwei Lan Jiahong Ma Wenqing Wei Rong Zhu Pengfei Li Bolin Ding Defu Lian Zhewei Wei Jingren Zhou 83 5 0 03 Jun 2024
Understanding and Minimising Outlier Features in Neural Network Training Bobby He Lorenzo Noci Daniele Paliotta Imanol Schlag Thomas Hofmann 105 4 0 29 May 2024
Deep Feature Gaussian Processes for Single-Scene Aerosol Optical Depth Reconstruction Shengjie Liu Lu Zhang 34 2 0 27 May 2024
Large Deviations of Gaussian Neural Networks with ReLU activation Quirin Vogel 55 1 0 27 May 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 140 2 0 27 May 2024
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers Lorenzo Tiberi Francesca Mignacco Kazuki Irie H. Sompolinsky 107 7 0 24 May 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning Shuai Zhang Heshan Devaka Fernando Miao Liu K. Murugesan Songtao Lu Pin-Yu Chen Tianyi Chen Meng Wang 84 2 0 24 May 2024
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh 66 0 0 24 May 2024
Scalable Optimization in the Modular Norm Tim Large Yang Liu Minyoung Huh Hyojin Bahng Phillip Isola Jeremy Bernstein 92 16 0 23 May 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 229 3 0 20 May 2024
A Method on Searching Better Activation Functions Haoyuan Sun Zihao Wu Bo Xia Pu Chang Zibin Dong Yifu Yuan Yongzhe Chang Xueqian Wang 75 3 0 19 May 2024
Random ReLU Neural Networks as Non-Gaussian Processes Rahul Parhi Pakshal Bohra Ayoub El Biari Mehrsa Pourya Michael Unser 131 1 0 16 May 2024
Restoring balance: principled under/oversampling of data for optimal classification Emanuele Loffredo Mauro Pastore Simona Cocco R. Monasson 117 9 0 15 May 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 180 2 0 15 May 2024
Wilsonian Renormalization of Neural Network Gaussian Processes Jessica N. Howard Ro Jefferson Anindita Maiti Zohar Ringel BDL 182 3 0 09 May 2024
Multi-layer random features and the approximation power of neural networks Rustem Takhanov 69 1 0 26 Apr 2024
The Positivity of the Neural Tangent Kernel Luís Carvalho Joao L. Costa José Mourao Gonccalo Oliveira 104 3 0 19 Apr 2024
BayesJudge: Bayesian Kernel Language Modelling with Confidence Uncertainty in Legal Judgment Prediction Ubaid Azam Imran Razzak Shelly Vishwakarma Hakim Hacid Dell Zhang Shoaib Jameel UQCV ELM BDL 77 0 0 16 Apr 2024
Log-PDE Methods for Rough Signature Kernels M. Lemercier Terry Lyons C. Salvi 205 2 0 01 Apr 2024
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification Yibo Miao Yu Lei Feng Zhou Zhijie Deng VLM UQCV BDL 109 3 0 30 Mar 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 144 0 0 28 Mar 2024
A Unified Kernel for Neural Network Learning Shao-Qun Zhang Zong-Yi Chen Yong-Ming Tian Xun Lu 95 1 0 26 Mar 2024
Approximation with Random Shallow ReLU Networks with Applications to Model Reference Adaptive Control Andrew G. Lamperski Tyler Lekang 76 3 0 25 Mar 2024
Improving Forward Compatibility in Class Incremental Learning by Increasing Representation Rank and Feature Richness Jaeill Kim Wonseok Lee Moonjung Eo Wonjong Rhee CLL 123 0 0 22 Mar 2024
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks Biswadeep Chakraborty Saibal Mukhopadhyay 90 3 0 19 Mar 2024
Neural network representation of quantum systems Koji Hashimoto Yuji Hirono Jun Maeda Jojiro Totsuka-Yoshinaka 87 2 0 18 Mar 2024
Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression S. Z. Ashtiani Mohammad Sarabian K. Laksari H. Babaee 59 4 0 14 Mar 2024
Transformers Learn Low Sensitivity Functions: Investigations and Implications Bhavya Vasudeva Deqing Fu Tianyi Zhou Elliott Kau Youqi Huang Vatsal Sharan 118 2 0 11 Mar 2024
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts H. Bui Anqi Liu OOD BDL UQCV 195 4 0 07 Mar 2024
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks Lisa Schneckenreiter Richard Freinschlag Florian Sestak Johannes Brandstetter Günter Klambauer Andreas Mayr 117 5 0 07 Mar 2024
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN Biswadeep Chakraborty Beomseok Kang H. Kumar Saibal Mukhopadhyay 131 11 0 06 Mar 2024
Emergent Equivariance in Deep Ensembles Jan E. Gerken Pan Kessel UQCV MDE 106 8 0 05 Mar 2024