On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

50 / 1,250 papers shown

Title
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier Alain Durmus Eric Moulines FedML 21 6 0 31 Oct 2022
Radically Lower Data-Labeling Costs for Visually Rich Document Extraction Models Yichao Zhou James Bradley Wendt Navneet Potti Jing Xie Sandeep Tata VLM 32 1 0 28 Oct 2022
Stop Measuring Calibration When Humans Disagree Joris Baan Wilker Aziz Barbara Plank Raquel Fernández 29 53 0 28 Oct 2022
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs Hans Hao-Hsun Hsu Yuesong Shen Daniel Cremers 34 7 0 27 Oct 2022
Private Isotonic Regression Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 27 0 0 27 Oct 2022
Exploiting Features and Logits in Heterogeneous Federated Learning Yun-Hin Chan Edith C.H. Ngai FedML 32 2 0 27 Oct 2022
Useful Confidence Measures: Beyond the Max Score G. Yona Amir Feder Itay Laish 81 5 0 25 Oct 2022
Revisiting Softmax for Uncertainty Approximation in Text Classification Andreas Nugaard Holm Dustin Wright Isabelle Augenstein BDL UQCV 24 9 0 25 Oct 2022
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data Huy Hoang Nguyen Matthew B. Blaschko S. Saarakkala A. Tiulpin MedIm AI4CE 50 15 0 25 Oct 2022
Bridging Machine Learning and Sciences: Opportunities and Challenges Taoli Cheng UQCV OOD AI4CE 27 2 0 24 Oct 2022
Are Deep Sequence Classifiers Good at Non-Trivial Generalization? Francesco Cazzaro A. Quattoni X. Carreras MQ 26 0 0 24 Oct 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 50 19 0 23 Oct 2022
Federated Calibration and Evaluation of Binary Classifiers Graham Cormode Igor L. Markov FedML 38 4 0 22 Oct 2022
Considerations for Visualizing Uncertainty in Clinical Machine Learning Models Caitlin F. Harrigan Gabriela Morgenshtern Anna Goldenberg Fanny Chevalier HAI 17 3 0 21 Oct 2022
Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier Sumedha Singla Nihal Murali Forough Arabshahi Sofia Triantafyllou Kayhan Batmanghelich CML 59 5 0 21 Oct 2022
Calibration tests beyond classification David Widmann Fredrik Lindsten Dave Zachariah 30 17 0 21 Oct 2022
Large Language Models Can Self-Improve Jiaxin Huang S. Gu Le Hou Yuexin Wu Xuezhi Wang Hongkun Yu Jiawei Han ReLM AI4MH LRM 47 568 0 20 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity Dennis Ulmer J. Frellsen Christian Hardmeier 197 22 0 20 Oct 2022
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions Paweł Antoni Pierzchlewicz R. J. Cotton Mohammad Ali Bashiri Fabian H. Sinz 3DH 21 8 0 20 Oct 2022
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui Gezheng Xu Qi Chen Jiaqi Li Charles Ling Tal Arbel Boyu Wang Christian Gagné 46 37 0 19 Oct 2022
Fine-tune your Classifier: Finding Correlations With Temperature Benjamin Chamand Olivier Risser-Maroix Camille Kurtz P. Joly Nicolas Loménie 38 2 0 18 Oct 2022
Packed-Ensembles for Efficient Uncertainty Estimation Olivier Laurent Adrien Lafage Enzo Tartaglione Geoffrey Daniel Jean-Marc Martinez Andrei Bursuc Gianni Franchi OODD 46 32 0 17 Oct 2022
Prompting GPT-3 To Be Reliable Chenglei Si Zhe Gan Zhengyuan Yang Shuohang Wang Jianfeng Wang Jordan L. Boyd-Graber Lijuan Wang KELM LRM 60 283 0 17 Oct 2022
Sequential Learning Of Neural Networks for Prequential MDL J. Bornschein Yazhe Li Marcus Hutter AI4TS 27 6 0 14 Oct 2022
The Open-World Lottery Ticket Hypothesis for OOD Intent Classification Yunhua Zhou Pengyu Wang Peiju Liu Yuxin Wang Xipeng Qiu 30 2 0 13 Oct 2022
Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes Yifang Sun Wei Wang OODD 29 5 0 13 Oct 2022
TiDAL: Learning Training Dynamics for Active Learning Seong Min Kye Kwanghee Choi Hyeongmin Byun Buru Chang 34 13 0 13 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 36 24 0 12 Oct 2022
Curved Representation Space of Vision Transformers Juyeop Kim Junha Park Songkuk Kim Jongseok Lee ViT 41 6 0 11 Oct 2022
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis Yuxin Xiao Paul Pu Liang Umang Bhatt Willie Neiswanger Ruslan Salakhutdinov Louis-Philippe Morency 175 86 0 10 Oct 2022
Uncertainty-aware LiDAR Panoptic Segmentation Kshitij Sirohi Sajad Marvi Daniel Buscher Wolfram Burgard 3DPC UQCV 34 6 0 10 Oct 2022
Class-wise and reduced calibration methods Michael Panchenko Anes Benmerzoug Miguel de Benito Delgado 23 0 0 07 Oct 2022
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture M. Jung He Zhao Joanna Dipnall Belinda Gabbe Lan Du UQCV EDL 67 12 0 06 Oct 2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 34 80 0 05 Oct 2022
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models Chen Liang Wenguan Wang Jiaxu Miao Yi Yang VLM 41 117 0 05 Oct 2022
Meta-Ensemble Parameter Learning Zhengcong Fei Shuman Tian Junshi Huang Xiaoming Wei Xiaolin K. Wei OOD 44 2 0 05 Oct 2022
The Calibration Generalization Gap Annabelle Carrell Neil Rohit Mallinar James Lucas Preetum Nakkiran UQCV 34 18 0 05 Oct 2022
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction Edward James Smith M. Drozdzal Derek Nowrouzezahrai David Meger Adriana Romero Soriano 59 9 0 03 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 32 4 0 30 Sep 2022
Variable-Based Calibration for Machine Learning Classifiers Mark Kelly Padhraic Smyth 27 4 0 30 Sep 2022
Bayesian Neural Network Versus Ex-Post Calibration For Prediction Uncertainty Satya Borgohain Klaus Ackermann Rubén Loaiza-Maya BDL UQCV 18 0 0 29 Sep 2022
Downstream Datasets Make Surprisingly Good Pretraining Corpora Kundan Krishna Saurabh Garg Jeffrey P. Bigham Zachary Chase Lipton 50 30 0 28 Sep 2022
Transfer Learning with Pretrained Remote Sensing Transformers A. Fuller K. Millard J.R. Green 35 11 0 28 Sep 2022
Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration Yu Tang Pin-Yu Chen Tsung-Yi Ho 31 5 0 23 Sep 2022
Extremely Simple Activation Shaping for Out-of-Distribution Detection Andrija Djurisic Nebojsa Bozanic Arjun Ashok Rosanne Liu OODD 172 151 0 20 Sep 2022
Probabilistic Dalek -- Emulator framework with probabilistic prediction for supernova tomography W. E. Kerzendorf Nutan Chen Jack O'Brien J. Buchner Patrick van der Smagt MedIm 20 0 0 20 Sep 2022
Improving the Performance of DNN-based Software Services using Automated Layer Caching M. Abedi Yanni Iouannou Pooyan Jamshidi Hadi Hemmati 28 0 0 18 Sep 2022
Non-invasive Localization of the Ventricular Excitation Origin Without Patient-specific Geometries Using Deep Learning N. Pilia S. Schuler Maike Rees Gerald Moik D. Potyagaylo O. Dössel A. Loewe 21 14 0 16 Sep 2022
On the Relation between Sensitivity and Accuracy in In-context Learning Yanda Chen Chen Zhao Zhou Yu Kathleen McKeown He He 182 77 0 16 Sep 2022
Towards Improving Calibration in Object Detection Under Domain Shift Muhammad Akhtar Munir M. H. Khan M. Sarfraz Mohsen Ali 19 22 0 15 Sep 2022