On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

50 / 154 papers shown

Title
Optimizing Calibration by Gaining Aware of Prediction Correctness Yuchi Liu Lei Wang Yuli Zou James Zou Liang Zheng UQCV 77 2 0 19 Apr 2024
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models Jingyang Zhang Jingwei Sun Eric C. Yeats Ouyang Yang Martin Kuo Jianyi Zhang Hao Frank Yang Hai "Helen" Li 85 49 0 03 Apr 2024
Enabling Uncertainty Estimation in Iterative Neural Networks Nikita Durasov Doruk Öner Jonathan Donier Hieu M. Le Pascal Fua UQCV 167 9 0 25 Mar 2024
Uncertainty in Graph Neural Networks: A Survey Fangxin Wang Yuqing Liu Kay Liu Yibo Wang Sourav Medya Philip S. Yu AI4CE 106 10 0 11 Mar 2024
Federated Learning over Connected Modes Dennis Grinwald Philipp Wiesner Shinichi Nakajima FedML 128 0 0 05 Mar 2024
Towards Calibrated Deep Clustering Network Yuheng Jia Jianhong Cheng Hui Liu Junhui Hou UQCV 86 1 0 04 Mar 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 189 21 0 28 Feb 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 81 7 0 02 Feb 2024
Prevalidated ridge regression is a highly-efficient drop-in replacement for logistic regression for high-dimensional data Angus Dempster Geoffrey I. Webb Daniel F. Schmidt 49 0 0 28 Jan 2024
NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks Matteo Gambella Jary Pomponi Simone Scardapane Manuel Roveri 51 2 0 24 Jan 2024
Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy Will LeVine Benjamin Pikus Jacob Phillips Berk Norman Fernando Amat Gil Sean Hendryx OODD 129 1 0 22 Jan 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift Renchunzi Xie Ambroise Odonnat Vasilii Feofanov I. Redko Jianfeng Zhang Bo An UQCV 113 1 0 17 Jan 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 96 3 0 16 Jan 2024
An Invitation to Deep Reinforcement Learning Bernhard Jaeger Andreas Geiger OffRL OOD 111 5 0 13 Dec 2023
Class Uncertainty: A Measure to Mitigate Class Imbalance Z. S. Baltaci K. Oksuz S. Kuzucu K. Tezoren B. K. Konar A. Ozkan Emre Akbas Sinan Kalkan 116 2 0 23 Nov 2023
Predicting generalization performance with correctness discriminators Yuekun Yao Alexander Koller 81 1 0 15 Nov 2023
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 92 1 0 02 Nov 2023
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI F. Terhag P. Knechtges A. Basermann R. Tempone 118 1 0 30 Oct 2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks Souradeep Dutta Michele Caprio Vivian Lin Matthew Cleaveland Kuk Jin Jang I. Ruchkin O. Sokolsky Insup Lee OOD AAML 173 8 0 28 Aug 2023
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration Hiroki Naganuma Ryuichiro Hataya Kotaro Yoshida Ioannis Mitliagkas OODD 151 3 0 17 Jul 2023
Calibration Error Estimation Using Fuzzy Binning Geetanjali Bihani Julia Taylor Rayz 154 2 0 30 Apr 2023
Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation Wenbo Hu Xin Sun Qiang liu Wenbo Hu Shu Wu 74 0 0 23 Mar 2023
Improving Multi-task Learning via Seeking Task-based Flat Regions Hoang Phan Lam C. Tran Ngoc N. Tran Nhat Ho Tuan Truong Qi Lei Nhat Ho Dinh Q. Phung Trung Le 182 11 0 24 Nov 2022
Exploiting Features and Logits in Heterogeneous Federated Learning Yun-Hin Chan Edith C.H. Ngai FedML 65 2 0 27 Oct 2022
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers Markus Kängsepp Kaspar Valk Meelis Kull 64 3 0 16 Mar 2022
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation Volodymyr Kuleshov Shachi Deshpande UQCV BDL 386 34 0 14 Dec 2021
Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions Kaustubh D. Dhole 116 25 0 17 Aug 2020
HAPI: Hardware-Aware Progressive Inference Stefanos Laskaridis Stylianos I. Venieris Hyeji Kim Nicholas D. Lane 55 46 0 10 Aug 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 156 447 0 17 Jun 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 66 84 0 16 Jun 2020
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 340 4,700 0 15 Mar 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 153 1,137 0 23 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 729 5,798 0 05 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 322 4,624 0 10 Nov 2016
Stochastic Variational Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 96 267 0 01 Nov 2016
Learning Scalable Deep Kernels with Recurrent Structure Maruan Al-Shedivat A. Wilson Yunus Saatchi Zhiting Hu Eric Xing BDL 53 104 0 27 Oct 2016
Achieving Human Parity in Conversational Speech Recognition Wayne Xiong J. Droppo Xuedong Huang Frank Seide M. Seltzer A. Stolcke Dong Yu Geoffrey Zweig 78 579 0 17 Oct 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 143 3,441 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 723 36,708 0 25 Aug 2016
Estimating Uncertainty Online Against an Adversary Volodymyr Kuleshov Stefano Ermon OOD 38 7 0 13 Jul 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 320 7,971 0 23 May 2016
End to End Learning for Self-Driving Cars Mariusz Bojarski D. Testa Daniel Dworakowski Bernhard Firner B. Flepp ... Urs Muller Jiakai Zhang Xin Zhang Jake Zhao Karol Zieba SSL 85 4,163 0 25 Apr 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 199 2,352 0 30 Mar 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.0K 193,426 0 10 Dec 2015
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 230 885 0 06 Nov 2015
Modelling Uncertainty in Deep Learning for Camera Relocalization Alex Kendall R. Cipolla BDL 45 540 0 19 Sep 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 722 9,290 0 06 Jun 2015
Highway Networks R. Srivastava Klaus Greff Jürgen Schmidhuber 167 1,768 0 03 May 2015
Fast R-CNN Ross B. Girshick ObjD 290 25,033 0 30 Apr 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 318 19,609 0 09 Mar 2015