暂无分享,去创建一个
Silvio Savarese | Stefano Ermon | Huan Wang | Caiming Xiong | Yu Bai | Shengjia Zhao | Rachel Luo | Aadyot Bhatnagar | S. Savarese | S. Ermon | Caiming Xiong | Shengjia Zhao | Yu Bai | Haiquan Wang | Rachel Luo | Aadyot Bhatnagar | Stefano Ermon
[1] Alexei A. Efros,et al. What makes ImageNet good for transfer learning? , 2016, ArXiv.
[2] Stefano Ermon,et al. Individual Calibration with Randomized Forecasting , 2020, ICML.
[3] Yiming Yang,et al. On the Sentence Embeddings from BERT for Semantic Textual Similarity , 2020, EMNLP.
[4] Guy N. Rothblum,et al. Calibration for the (Computationally-Identifiable) Masses , 2017, ArXiv.
[5] Peter A. Flach,et al. Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration , 2019, NeurIPS.
[6] G. Brier. VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY , 1950 .
[7] Sunita Sarawagi,et al. Trainable Calibration Measures For Neural Networks From Kernel Mean Embeddings , 2018, ICML.
[8] Berkman Sahiner,et al. Calibration of medical diagnostic classifier scores to the probability of disease , 2016, Statistical methods in medical research.
[9] M. Ringnér,et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks , 2001, Nature Medicine.
[10] Milos Hauskrecht,et al. Obtaining Well Calibrated Probabilities Using Bayesian Binning , 2015, AAAI.
[11] Kilian Q. Weinberger,et al. On Calibration of Modern Neural Networks , 2017, ICML.
[12] Andrey Malinin,et al. Ensemble Distribution Distillation , 2019, ICLR.
[13] Alex Kendall,et al. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? , 2017, NIPS.
[14] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[15] Bianca Zadrozny,et al. Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers , 2001, ICML.
[16] Henri Berestycki,et al. Asymptotics and calibration of local volatility models , 2002 .
[17] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[18] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[19] A. Raftery,et al. Probabilistic forecasts, calibration and sharpness , 2007 .
[20] Jon M. Kleinberg,et al. Inherent Trade-Offs in the Fair Determination of Risk Scores , 2016, ITCS.
[21] Fredrik Lindsten,et al. Calibration tests in multi-class classification: A unifying framework , 2019, NeurIPS.
[22] Bianca Zadrozny,et al. Transforming classifier scores into accurate multiclass probability estimates , 2002, KDD.
[23] Eric P. Xing,et al. Real-to-Virtual Domain Unification for End-to-End Autonomous Driving , 2018, ECCV.
[24] Marc Niethammer,et al. Local Temperature Scaling for Probability Calibration , 2020, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[25] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[26] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .