Ensemble Distribution Distillation

30 April 2019

Papers citing "Ensemble Distribution Distillation"

42 / 42 papers shown

Title
Quantifying Knowledge Distillation Using Partial Information Decomposition Pasan Dissanayake Faisal Hamman Barproda Halder Ilia Sucholutsky Qiuyi Zhang Sanghamitra Dutta 36 0 0 12 Nov 2024
Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling Guiyu Zhang Huan-ang Gao Zijian Jiang Hao Zhao Zhedong Zheng EGVM 44 6 0 15 Oct 2024
Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection A. Benfenati P. Causin Hang Yu Zhedong Zheng 3DPC 42 2 0 01 Aug 2024
Learning to Project for Cross-Task Knowledge Distillation Dylan Auty Roy Miles Benedikt Kolbeinsson K. Mikolajczyk 40 0 0 21 Mar 2024
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex Yasushi Esaki Akihiro Nakamura Keisuke Kawano Ryoko Tokuhisa Takuro Kutsuna 38 0 0 21 Feb 2024
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 24 0 0 01 Aug 2023
Function-Space Regularization for Deep Bayesian Classification J. Lin Joe Watson Pascal Klink Jan Peters UQCV BDL 35 1 0 12 Jul 2023
Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble Jiahua Dong Guohua Cheng Yue Zhang Chengtao Peng Yu Song Ruofeng Tong Lanfen Lin Yen-Wei Chen 24 0 0 14 Apr 2023
Distilling Calibrated Student from an Uncalibrated Teacher Ishan Mishra Sethu Vamsi Krishna Deepak Mishra FedML 32 2 0 22 Feb 2023
Towards Inference Efficient Deep Ensemble Learning Ziyue Li Kan Ren Yifan Yang Xinyang Jiang Yuqing Yang Dongsheng Li BDL 21 12 0 29 Jan 2023
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification Xue Li Wei Shen Denis Xavier Charles UQCV EDL 30 3 0 12 Sep 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? Lisa Wimmer Yusuf Sale Paul Hofman Bern Bischl Eyke Hüllermeier PER UD 34 64 0 07 Sep 2022
An Impartial Take to the CNN vs Transformer Robustness Contest Francesco Pinto Philip H. S. Torr P. Dokania UQCV AAML 22 48 0 22 Jul 2022
Latent Discriminant deterministic Uncertainty Gianni Franchi Xuanlong Yu Andrei Bursuc Emanuel Aldea Séverine Dubuisson David Filliat UQCV 22 18 0 20 Jul 2022
Shifts 2.0: Extending The Dataset of Real Distributional Shifts A. Malinin A. Athanasopoulos M. Barakovic Meritxell Bach Cuadra Mark J. F. Gales ... Francesco La Rosa Eli Sivena V. Tsarsitalidis Efi Tsompopoulou E. Volf OOD 22 28 0 30 Jun 2022
Functional Ensemble Distillation Coby Penso Idan Achituve Ethan Fetaya FedML 23 2 0 05 Jun 2022
Distributed Training for Deep Learning Models On An Edge Computing Network Using ShieldedReinforcement Learning Tanmoy Sen Haiying Shen OffRL 11 5 0 01 Jun 2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation Martin Ferianc Miguel R. D. Rodrigues UQCV 37 0 0 19 May 2022
Trusted Multi-View Classification with Dynamic Evidential Fusion Zongbo Han Changqing Zhang H. Fu Joey Tianyi Zhou EDL 17 217 0 25 Apr 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation Yassir Fathullah Mark J. F. Gales UQCV 14 11 0 15 Mar 2022
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation Viktor Bengs Eyke Hüllermeier Willem Waegeman EDL UQCV UD 16 36 0 11 Mar 2022
GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting Zhao Chen Vincent Casser Henrik Kretzschmar Dragomir Anguelov 26 5 0 16 Jan 2022
Diversity Matters When Learning From Ensembles G. Nam Jongmin Yoon Yoonho Lee Juho Lee UQCV FedML VLM 37 36 0 27 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 28 80 0 26 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 26 11 0 06 Oct 2021
Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performance Carel van Niekerk A. Malinin Christian Geishauser Michael Heck Hsien-chin Lin Nurul Lubis Shutong Feng Milica Gavsić 18 9 0 09 Sep 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 23 688 0 04 Sep 2021
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 30 1,109 0 07 Jul 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 41 93 0 22 Jun 2021
Distilling a Powerful Student Model via Online Knowledge Distillation Shaojie Li Mingbao Lin Yan Wang Yongjian Wu Yonghong Tian Ling Shao Rongrong Ji FedML 25 46 0 26 Mar 2021
Posterior Meta-Replay for Continual Learning Christian Henning Maria R. Cervera Francesco DÁngelo J. Oswald Regina Traber Benjamin Ehret Seijin Kobayashi Benjamin Grewe João Sacramento CLL BDL 51 54 0 01 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip H. S. Torr Y. Gal UD UQCV PER BDL 18 145 0 23 Feb 2021
Local Calibration: Metrics and Recalibration Rachel Luo Aadyot Bhatnagar Yu Bai Shengjia Zhao Huan Wang Caiming Xiong Silvio Savarese Stefano Ermon Edward Schmerling Marco Pavone 11 14 0 22 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 200 81 0 16 Feb 2021
Densely Guided Knowledge Distillation using Multiple Teacher Assistants Wonchul Son Jaemin Na Junyong Choi Wonjun Hwang 20 110 0 18 Sep 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks Meet P. Vadera Adam D. Cobb B. Jalaeian Benjamin M. Marlin BDL UQCV 19 16 0 08 Jul 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 15 94 0 18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 17 169 0 16 Jun 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 17 20 0 16 May 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 22 559 0 26 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 279 9,136 0 06 Jun 2015