Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles

9 November 2018

Papers citing "Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles"

8 / 8 papers shown

Title
Evaluating the effect of data augmentation and BALD heuristics on distillation of Semantic-KITTI dataset Ngoc Phuong Anh Duong Alexandre Almin Léo Lemarié B. R. Kiran 27 0 0 21 Feb 2023
Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling Haw-Shiuan Chang Ruei-Yao Sun Kathryn Ricci Andrew McCallum 43 14 0 10 Oct 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 59 1,111 0 07 Jul 2021
Neural Active Learning with Performance Guarantees Pranjal Awasthi Christoph Dann Claudio Gentile Ayush Sekhari Zhilei Wang 26 22 0 06 Jun 2021
Training Data Subset Search with Ensemble Active Learning Kashyap Chitta J. Álvarez Elmar Haussmann C. Farabet 22 13 0 29 May 2019
Constraining the Parameters of High-Dimensional Models with Active Learning S. Caron Tom Heskes Sydney Otten B. Stienen AI4CE 16 27 0 19 May 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015