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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Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise Yilong Hou Xi’an Li Jinran Wu You-Gan Wang 69 1 0 18 Aug 2024
DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks Shrenik Zinage Sudeepta Mondal S. Sarkar 46 6 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 36 2 0 26 Jul 2024
Gaussian Process Kolmogorov-Arnold Networks Andrew Siyuan Chen 29 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 44 5 0 24 Jul 2024
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing Biswadeep Chakraborty Saibal Mukhopadhyay 38 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 52 0 0 05 Jul 2024
Coding schemes in neural networks learning classification tasks Alexander van Meegen H. Sompolinsky 44 6 0 24 Jun 2024
Equivariant Neural Tangent Kernels Philipp Misof Pan Kessel Jan E. Gerken 64 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 45 3 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 33 5 0 03 Jun 2024
Understanding and Minimising Outlier Features in Neural Network Training Bobby He Lorenzo Noci Daniele Paliotta Imanol Schlag Thomas Hofmann 47 3 0 29 May 2024
Deep Feature Gaussian Processes for Single-Scene Aerosol Optical Depth Reconstruction Shengjie Liu Lu Zhang 22 2 0 27 May 2024
Large Deviations of Gaussian Neural Networks with ReLU activation Quirin Vogel 36 1 0 27 May 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 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 46 6 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 54 1 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 34 0 0 24 May 2024
Scalable Optimization in the Modular Norm Tim Large Yang Liu Minyoung Huh Hyojin Bahng Phillip Isola Jeremy Bernstein 54 12 0 23 May 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 53 2 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 17 3 0 19 May 2024
Random ReLU Neural Networks as Non-Gaussian Processes Rahul Parhi Pakshal Bohra Ayoub El Biari Mehrsa Pourya Michael Unser 63 1 0 16 May 2024
Restoring balance: principled under/oversampling of data for optimal classification Emanuele Loffredo Mauro Pastore Simona Cocco R. Monasson 48 9 0 15 May 2024
Spectral complexity of deep neural networks Simmaco Di Lillo Domenico Marinucci Michele Salvi Stefano Vigogna BDL 82 1 0 15 May 2024
Wilsonian Renormalization of Neural Network Gaussian Processes Jessica N. Howard Ro Jefferson Anindita Maiti Zohar Ringel BDL 85 3 0 09 May 2024
Multi-layer random features and the approximation power of neural networks Rustem Takhanov 34 1 0 26 Apr 2024
The Positivity of the Neural Tangent Kernel Luís Carvalho Joao L. Costa José Mourao Gonccalo Oliveira 48 1 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 39 0 0 16 Apr 2024
A High Order Solver for Signature Kernels M. Lemercier Terry Lyons 31 3 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 51 2 0 30 Mar 2024
Tensor Network-Constrained Kernel Machines as Gaussian Processes Frederiek Wesel Kim Batselier 30 0 0 28 Mar 2024
A Unified Kernel for Neural Network Learning Shao-Qun Zhang Zong-Yi Chen Yong-Ming Tian Xun Lu 36 1 0 26 Mar 2024
Approximation with Random Shallow ReLU Networks with Applications to Model Reference Adaptive Control Andrew G. Lamperski Tyler Lekang 35 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 54 0 0 22 Mar 2024
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks Biswadeep Chakraborty Saibal Mukhopadhyay 37 3 0 19 Mar 2024
Neural network representation of quantum systems Koji Hashimoto Yuji Hirono Jun Maeda Jojiro Totsuka-Yoshinaka 41 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 34 2 0 14 Mar 2024
Transformers Learn Low Sensitivity Functions: Investigations and Implications Bhavya Vasudeva Deqing Fu Tianyi Zhou Elliott Kau Youqi Huang Vatsal Sharan 32 4 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 49 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 46 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 46 8 0 06 Mar 2024
Emergent Equivariance in Deep Ensembles Jan E. Gerken Pan Kessel UQCV MDE 43 6 0 05 Mar 2024
A prediction rigidity formalism for low-cost uncertainties in trained neural networks Filippo Bigi Sanggyu Chong Michele Ceriotti Federico Grasselli 52 5 0 04 Mar 2024
Robustness bounds on the successful adversarial examples in probabilistic models: Implications from Gaussian processes Hiroaki Maeshima Akira Otsuka AAML 40 0 0 04 Mar 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 103 19 0 04 Mar 2024
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach Lingyu Gu Yongqiang Du Yuan Zhang Di Xie Shiliang Pu Robert C. Qiu Zhenyu Liao 46 6 0 01 Mar 2024
Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle Zeyu Zheng Khimya Khetarpal H. V. Hasselt Razvan Pascanu James Martens Will Dabney AI4CE 57 32 0 29 Feb 2024
Deep Neural Network Initialization with Sparsity Inducing Activations Ilan Price Nicholas Daultry Ball Samuel C.H. Lam Adam C. Jones Jared Tanner AI4CE 31 1 0 25 Feb 2024
Asymptotics of Learning with Deep Structured (Random) Features Dominik Schröder Daniil Dmitriev Hugo Cui Bruno Loureiro 61 6 0 21 Feb 2024
Gaussian Process Neural Additive Models Wei Zhang Brian Barr John Paisley MedIm BDL 19 7 0 19 Feb 2024