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2002.11531
Cited By

A general framework for ensemble distribution distillation

v1v2 (latest)

A general framework for ensemble distribution distillation

International Workshop on Machine Learning for Signal Processing (MLSP), 2020

26 February 2020

Jakob Lindqvist

Fredrik Lindsten

Lennart Svensson

ArXiv (abs)PDF HTML

Papers citing "A general framework for ensemble distribution distillation"

15 / 15 papers shown

Ensemble Distribution Distillation for Self-Supervised Human Activity Recognition

Ensemble Distribution Distillation for Self-Supervised Human Activity Recognition

Robert Davidson

152

0

0

10 Sep 2025

A Comprehensive Survey on Evidential Deep Learning and Its Applications

A Comprehensive Survey on Evidential Deep Learning and Its Applications

456

15

0

07 Sep 2024

Gaussian Mixture based Evidential Learning for Stereo Matching

Gaussian Mixture based Evidential Learning for Stereo Matching

245

0

0

05 Aug 2024

Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex

Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex

Akihiro Nakamura

367

3

0

21 Feb 2024

Reliability Quantification of Deep Reinforcement Learning-based Control

Reliability Quantification of Deep Reinforcement Learning-based Control

Hitoshi Yoshioka

Hirotada Hashimoto

198

0

0

29 Sep 2023

Uncertainty Quantification for Image-based Traffic Prediction across
Cities

Uncertainty Quantification for Image-based Traffic Prediction across Cities

Alexander Timans

215

1

0

11 Aug 2023

ELFNet: Evidential Local-global Fusion for Stereo Matching

ELFNet: Evidential Local-global Fusion for Stereo MatchingIEEE International Conference on Computer Vision (ICCV), 2023

Fayao Liu

Jun Cheng

255

35

0

01 Aug 2023

Logit-Based Ensemble Distribution Distillation for Robust Autoregressive
Sequence Uncertainties

Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence UncertaintiesConference on Uncertainty in Artificial Intelligence (UAI), 2023

Yassir Fathullah

195

6

0

17 May 2023

Self-Aware Trajectory Prediction for Safe Autonomous Driving

Self-Aware Trajectory Prediction for Safe Autonomous Driving

Jun Li

236

12

0

16 May 2023

Compensation Learning in Semantic Segmentation

Compensation Learning in Semantic Segmentation

Christoph Reinders

215

6

0

26 Apr 2023

Knowledge Distillation from Multiple Foundation Models for End-to-End
Speech Recognition

Knowledge Distillation from Multiple Foundation Models for End-to-End Speech Recognition

Xiaoyu Yang

206

11

0

20 Mar 2023

TEDL: A Two-stage Evidential Deep Learning Method for Classification
Uncertainty Quantification

TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification

Denis Xavier Charles

222

3

0

12 Sep 2022

Simple Regularisation for Uncertainty-Aware Knowledge Distillation

Simple Regularisation for Uncertainty-Aware Knowledge Distillation

Miguel R. D. Rodrigues

164

2

0

19 May 2022

A Survey of Uncertainty in Deep Neural Networks

A Survey of Uncertainty in Deep Neural Networks

Cedrique Rovile Njieutcheu Tassi

...

Muhammad Shahzad

566

1,534

0

07 Jul 2021

MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks

MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep SubnetworksIEEE International Conference on Computer Vision (ICCV), 2021

Alexandre Ramé

352

64

0

10 Mar 2021

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