Title
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Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration Shengjia Zhao Stefano Ermon 25 8 0 15 Nov 2020
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification G. Liang Yu Zhang Xiaoqin Wang Nathan Jacobs UQCV 39 61 0 09 Sep 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 72 561 0 30 Jun 2020
Calibration of Neural Networks using Splines Kartik Gupta Amir M. Rahimi Thalaiyasingam Ajanthan Thomas Mensink C. Sminchisescu Leonid Sigal 51 106 0 23 Jun 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 64 222 0 16 Mar 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 423 3,397 0 09 Mar 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 76 454 0 21 Feb 2020
Deep learning-based survival prediction for multiple cancer types using histopathology images Ellery Wulczyn David F. Steiner Zhaoyang Xu Apaar Sadhwani Hongwu Wang I. Flament C. Mermel Po-Hsuan Cameron Chen Yun-Hui Liu Martin C. Stumpe 25 213 0 16 Dec 2019
Machine Learning for Precipitation Nowcasting from Radar Images Shreya Agrawal Luke Barrington Carla Bromberg J. Burge Cenk Gazen Jason Hickey AI4Cl 46 223 0 11 Dec 2019
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 60 378 0 28 Oct 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 163 1,388 0 21 Oct 2019
Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation Janis Postels Francesco Ferroni Huseyin Coskun Nassir Navab Federico Tombari UQCV UD PER BDL 106 139 0 01 Aug 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 62 535 0 27 May 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 74 804 0 07 Feb 2019
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 142 626 0 01 Jul 2018
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression Emmanuel J. Candes Pragya Sur 34 140 0 25 Apr 2018
Attention-based Deep Multiple Instance Learning Maximilian Ilse Jakub M. Tomczak Max Welling 118 1,790 0 13 Feb 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 74 908 0 27 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 243 9,687 0 25 Oct 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 199 5,774 0 14 Jun 2017
Age Progression/Regression by Conditional Adversarial Autoencoder Zhifei Zhang Yang Song Hairong Qi GAN CVBM 31 1,109 0 27 Feb 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 114 1,133 0 23 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 493 5,748 0 05 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 269 4,620 0 10 Nov 2016
Natural-Parameter Networks: A Class of Probabilistic Neural Networks Hao Wang Xingjian Shi Dit-Yan Yeung BDL 51 83 0 02 Nov 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 497 27,231 0 02 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 476 9,233 0 06 Jun 2015