Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing

11 June 2023

Papers citing "Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing"

6 / 6 papers shown

Title
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems Hao Wang Yifei Ma Hao Ding Yuyang Wang 38 6 0 01 Feb 2022
NOMU: Neural Optimization-based Model Uncertainty Jakob Heiss Jakob Weissteiner Hanna Wutte Sven Seuken Josef Teichmann BDL 37 19 0 26 Feb 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 299 6,984 0 20 Apr 2018
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
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,273 0 09 Jun 2011