Deep Gamblers: Learning to Abstain with Portfolio Theory

29 June 2019

Papers citing "Deep Gamblers: Learning to Abstain with Portfolio Theory"

6 / 6 papers shown

Title
Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes Yuanpeng Tu Yuxi Li Boshen Zhang Liang Liu J. Zhang Y. Wang C. Zhao 41 3 0 03 Jan 2025
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 13 5 0 09 Feb 2024
Selective Classification Via Neural Network Training Dynamics Stephan Rabanser Anvith Thudi Kimia Hamidieh Adam Dziedzic Nicolas Papernot 8 21 0 26 May 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,696 0 15 Sep 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 243 9,042 0 06 Jun 2015