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Approximate Conditional Coverage & Calibration via Neural Model
  Approximations
v1v2v3 (latest)

Approximate Conditional Coverage & Calibration via Neural Model Approximations

28 May 2022
A. Schmaltz
Danielle Rasooly
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Approximate Conditional Coverage & Calibration via Neural Model Approximations"

16 / 16 papers shown
Title
A Gentle Introduction to Conformal Prediction and Distribution-Free
  Uncertainty Quantification
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Anastasios Nikolas Angelopoulos
Stephen Bates
OOD
213
624
0
15 Jul 2021
Localized Conformal Prediction: A Generalized Inference Framework for
  Conformal Prediction
Localized Conformal Prediction: A Generalized Inference Framework for Conformal Prediction
Leying Guan
249
81
0
15 Jun 2021
Distribution-free uncertainty quantification for classification under
  label shift
Distribution-free uncertainty quantification for classification under label shift
Aleksandr Podkopaev
Aaditya Ramdas
UQCV
64
86
0
04 Mar 2021
Uncertainty Sets for Image Classifiers using Conformal Prediction
Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Nikolas Angelopoulos
Stephen Bates
Jitendra Malik
Michael I. Jordan
UQCV
207
338
0
29 Sep 2020
Classification with Valid and Adaptive Coverage
Classification with Valid and Adaptive Coverage
Yaniv Romano
Matteo Sesia
Emmanuel J. Candès
387
327
0
03 Jun 2020
SemEval-2017 Task 4: Sentiment Analysis in Twitter
SemEval-2017 Task 4: Sentiment Analysis in Twitter
Sara Rosenthal
N. Farra
Preslav Nakov
VLM
92
799
0
02 Dec 2019
Learning the Difference that Makes a Difference with
  Counterfactually-Augmented Data
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data
Divyansh Kaushik
Eduard H. Hovy
Zachary Chase Lipton
CML
96
570
0
26 Sep 2019
Evaluating Protein Transfer Learning with TAPE
Evaluating Protein Transfer Learning with TAPE
Roshan Rao
Nicholas Bhattacharya
Neil Thomas
Yan Duan
Xi Chen
John F. Canny
Pieter Abbeel
Yun S. Song
SSL
94
807
0
19 Jun 2019
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,871
0
14 Jun 2017
Least Ambiguous Set-Valued Classifiers with Bounded Error Levels
Least Ambiguous Set-Valued Classifiers with Bounded Error Levels
Mauricio Sadinle
Jing Lei
Larry A. Wasserman
181
251
0
02 Sep 2016
Compositional Sequence Labeling Models for Error Detection in Learner
  Writing
Compositional Sequence Labeling Models for Error Detection in Learner Writing
Marek Rei
H. Yannakoudakis
57
109
0
20 Jul 2016
Large-scale probabilistic predictors with and without guarantees of
  validity
Large-scale probabilistic predictors with and without guarantees of validity
V. Vovk
Ivan Petej
Valentina Fedorova
49
43
0
01 Nov 2015
One Billion Word Benchmark for Measuring Progress in Statistical
  Language Modeling
One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling
Ciprian Chelba
Tomas Mikolov
M. Schuster
Qi Ge
T. Brants
P. Koehn
T. Robinson
190
1,109
0
11 Dec 2013
ADADELTA: An Adaptive Learning Rate Method
ADADELTA: An Adaptive Learning Rate Method
Matthew D. Zeiler
ODL
165
6,632
0
22 Dec 2012
Venn-Abers predictors
Venn-Abers predictors
V. Vovk
Ivan Petej
72
80
0
31 Oct 2012
Conditional validity of inductive conformal predictors
Conditional validity of inductive conformal predictors
V. Vovk
233
418
0
12 Sep 2012
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