Multi-Class Gaussian Process Classification Made Conjugate: Efficient
Inference via Data Augmentation

Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation

23 May 2019

Théo Galy-Fajou

Christian Donner

Papers citing "Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation"

12 / 12 papers shown

Title
Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou Quyu Kong Zhijie Deng Fengxiang He Peng Cui Jun Zhu 38 2 0 29 Aug 2023
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models Tong Ye Shijing Si Jianzong Wang Ning Cheng Zhitao Li Jing Xiao 77 2 0 15 Mar 2023
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision Wei Tang Weijia Zhang Min-Ling Zhang 19 12 0 18 Dec 2022
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision Jieyu Zhang Linxin Song Alexander Ratner 56 8 0 06 Oct 2022
Transductive Decoupled Variational Inference for Few-Shot Classification Ashutosh Kumar Singh Hadi Jamali Rad BDL VLM 43 17 0 22 Aug 2022
Easy Variational Inference for Categorical Models via an Independent Binary Approximation M. Wojnowicz Shuchin Aeron Eric L. Miller M. C. Hughes 33 2 0 31 May 2022
Adaptive Inducing Points Selection For Gaussian Processes Théo Galy-Fajou Manfred Opper 33 15 0 21 Jul 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 32 100 0 29 Jun 2021
Scalable Cross Validation Losses for Gaussian Process Models M. Jankowiak Geoff Pleiss 31 6 0 24 May 2021
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake C. Snell R. Zemel 35 63 0 20 Jul 2020
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models Théo Galy-Fajou F. Wenzel Manfred Opper 29 4 0 26 Feb 2020
Extreme Classification via Adversarial Softmax Approximation Robert Bamler Stephan Mandt 30 23 0 15 Feb 2020