Learning Invariances using the Marginal Likelihood

16 August 2018

Papers citing "Learning Invariances using the Marginal Likelihood"

20 / 20 papers shown

Title
A Complexity-Based Theory of Compositionality Eric Elmoznino Thomas Jiralerspong Yoshua Bengio Guillaume Lajoie CoGe 108 10 0 18 Oct 2024
A Kernel Theory of Modern Data Augmentation Tri Dao Albert Gu Alexander J. Ratner Virginia Smith Christopher De Sa Christopher Ré 110 193 0 16 Mar 2018
Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation F. Wenzel Théo Galy-Fajou Christian Donner Marius Kloft Manfred Opper 69 36 0 18 Feb 2018
Data Augmentation Generative Adversarial Networks Antreas Antoniou Amos Storkey Harrison Edwards MedIm GAN 140 1,073 0 12 Nov 2017
Convolutional Gaussian Processes Mark van der Wilk C. Rasmussen J. Hensman BDL 74 132 0 06 Sep 2017
Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes Hyunjik Kim Yee Whye Teh 57 52 0 08 Jun 2017
Local Group Invariant Representations via Orbit Embeddings Anant Raj Abhishek Kumar Youssef Mroueh Tom Fletcher Bernhard Schölkopf 53 38 0 06 Dec 2016
Understanding Probabilistic Sparse Gaussian Process Approximations Matthias Bauer Mark van der Wilk C. Rasmussen 54 259 0 15 Jun 2016
PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain Francis R. Bach Alexandre Lacoste Simon Lacoste-Julien 68 184 0 27 May 2016
Group Equivariant Convolutional Networks Taco S. Cohen Max Welling BDL 171 1,945 0 24 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation Søren Hauberg Oren Freifeld Anders Boesen Lindbo Larsen John W. Fisher III Lars Kai Hansen 57 154 0 09 Oct 2015
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation Scott W. Linderman Matthew J. Johnson Ryan P. Adams 55 98 0 18 Jun 2015
MCMC for Variationally Sparse Gaussian Processes J. Hensman A. G. Matthews Maurizio Filippone Zoubin Ghahramani 66 141 0 12 Jun 2015
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 314 7,392 0 05 Jun 2015
On Sparse variational methods and the Kullback-Leibler divergence between stochastic processes A. G. Matthews J. Hensman Richard Turner Zoubin Ghahramani 84 192 0 27 Apr 2015
Scalable Variational Gaussian Process Classification J. Hensman A. G. Matthews Zoubin Ghahramani BDL 75 645 0 07 Nov 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 107 1,235 0 26 Sep 2013
Invariances of random fields paths, with applications in Gaussian Process Regression D. Ginsbourger O. Roustant N. Durrande 99 11 0 06 Aug 2013