Neural Ensemble Search for Uncertainty Estimation and Dataset Shift

15 June 2020

Chris Holmes

Papers citing "Neural Ensemble Search for Uncertainty Estimation and Dataset Shift"

49 / 49 papers shown

Title
HopCast: Calibration of Autoregressive Dynamics Models Muhammad Bilal Shahid Cody H. Fleming UQCV 40 0 0 27 Jan 2025
Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning tasks Gregory Kang Ruey Lau Wenyang Hu Diwen Liu Jizhuo Chen S. Ng Bryan Kian Hsiang Low LRM AI4CE 76 7 0 12 Dec 2024
Dynamic Post-Hoc Neural Ensemblers Sebastian Pineda Arango Maciej Janowski Lennart Purucker Arber Zela Frank Hutter Josif Grabocka UQCV 36 0 0 06 Oct 2024
Scalable Ensemble Diversification for OOD Generalization and Detection Alexander Rubinstein Luca Scimeca Damien Teney Seong Joon Oh BDL OOD 355 1 0 25 Sep 2024
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble Chenhui Xu Fuxun Yu Zirui Xu Nathan Inkawhich Xiang Chen OODD 30 5 0 24 Mar 2024
Graph Neural Machine: A New Model for Learning with Tabular Data Giannis Nikolentzos Siyun Wang J. Lutzeyer Michalis Vazirgiannis 29 0 0 05 Feb 2024
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking Jacob Eisenstein Chirag Nagpal Alekh Agarwal Ahmad Beirami Alex DÁmour ... Katherine Heller Stephen R. Pfohl Deepak Ramachandran Peter Shaw Jonathan Berant 24 82 0 14 Dec 2023
Bayes' Rays: Uncertainty Quantification for Neural Radiance Fields Lily Goli Cody Reading Silvia Sellán Alec Jacobson Andrea Tagliasacchi BDL UQCV 23 59 0 06 Sep 2023
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation Jung Hyun Ryu Jaeheyoung Jeon Jewoong Cho Myung-joo Kang MoMe 11 1 0 05 Jul 2023
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu H. Fu Joey Tianyi Zhou Q. Hu 59 16 0 02 Jun 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis OOD UQCV 14 2 0 08 Apr 2023
Source-free Domain Adaptation Requires Penalized Diversity Laya Rafiee Sevyeri Ivaxi Sheth Farhood Farahnak Alexandre See Samira Ebrahimi Kahou T. Fevens Mohammad Havaei TTA 24 0 0 06 Apr 2023
A Survey of Historical Learning: Learning Models with Learning History Xiang Li Ge Wu Lingfeng Yang Wenzhe Wang Renjie Song Jian Yang MU AI4TS 23 2 0 23 Mar 2023
EPiC: Ensemble of Partial Point Clouds for Robust Classification Meir Yossef Levi Guy Gilboa 3DPC 15 10 0 20 Mar 2023
Bayesian Quadrature for Neural Ensemble Search Saad Hamid Xingchen Wan Martin Jørgensen Binxin Ru Michael A. Osborne BDL UQCV 28 1 0 15 Mar 2023
Deep incremental learning models for financial temporal tabular datasets with distribution shifts Thomas Wong Mauricio Barahona OOD AIFin AI4TS 18 0 0 14 Mar 2023
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning Danruo Deng Guangyong Chen Yang Yu Fu-Lun Liu Pheng-Ann Heng EDL UQCV FedML 27 40 0 03 Mar 2023
FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling Wei-Yin Ko Daniel D'souza Karina Nguyen Randall Balestriero Sara Hooker FedML 19 11 0 01 Mar 2023
A Survey on Uncertainty Quantification Methods for Deep Learning Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Yukun Li BDL UQCV AI4CE 19 18 0 26 Feb 2023
How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts? Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV 42 12 0 07 Feb 2023
DivBO: Diversity-aware CASH for Ensemble Learning Yu Shen Yupeng Lu Yang Li Yaofeng Tu Wentao Zhang Bin Cui 17 6 0 07 Feb 2023
Neural Architecture Search: Insights from 1000 Papers Colin White Mahmoud Safari R. Sukthanker Binxin Ru T. Elsken Arber Zela Debadeepta Dey Frank Hutter 3DV AI4CE 34 130 0 20 Jan 2023
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 27 5 0 15 Dec 2022
Pixel is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection Zhenyu Wu Lin Wang Wen Wang Qing Xia Chenglizhao Chen Aimin Hao Shuo Li AAML 36 5 0 13 Dec 2022
Automatic Neural Network Hyperparameter Optimization for Extrapolation: Lessons Learned from Visible and Near-Infrared Spectroscopy of Mango Fruit Matthew C. Dirks David Poole 18 16 0 03 Oct 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 32 260 0 05 Jul 2022
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation G. Nam Hyungi Lee Byeongho Heo Juho Lee UQCV FedML 18 7 0 30 Jun 2022
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview Florian Karl Tobias Pielok Julia Moosbauer Florian Pfisterer Stefan Coors ... Jakob Richter Michel Lang Eduardo C. Garrido-Merchán Juergen Branke B. Bischl AI4CE 26 56 0 15 Jun 2022
Revisiting the Importance of Amplifying Bias for Debiasing Jungsoo Lee Jeonghoon Park Daeyoung Kim Juyoung Lee E. Choi Jaegul Choo 37 21 0 29 May 2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation Martin Ferianc Miguel R. D. Rodrigues UQCV 37 0 0 19 May 2022
A Taxonomy of Error Sources in HPC I/O Machine Learning Models Mihailo Isakov Mikaela Currier Eliakin Del Rosario Sandeep Madireddy Prasanna Balaprakash P. Carns R. Ross Glenn K. Lockwood Michel A. Kinsy 22 1 0 18 Apr 2022
Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting Tanwi Mallick Prasanna Balaprakash Jane Macfarlane BDL 25 11 0 04 Apr 2022
Towards Less Constrained Macro-Neural Architecture Search Vasco Lopes L. A. Alexandre 28 5 0 10 Mar 2022
Evolutionary Neural Cascade Search across Supernetworks A. Chebykin T. Alderliesten Peter A. N. Bosman 13 1 0 08 Mar 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography Francisca Vasconcelos Bobby He Nalini Singh Yee Whye Teh BDL OOD UQCV 26 12 0 22 Feb 2022
Deep Ensembles Work, But Are They Necessary? Taiga Abe E. Kelly Buchanan Geoff Pleiss R. Zemel John P. Cunningham OOD UQCV 36 59 0 14 Feb 2022
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 19 139 0 20 Dec 2021
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification Romain Egele R. Maulik Krishnan Raghavan Bethany Lusch Isabelle M Guyon Prasanna Balaprakash UQCV OOD BDL 20 45 0 26 Oct 2021
No One Representation to Rule Them All: Overlapping Features of Training Methods Raphael Gontijo-Lopes Yann N. Dauphin E. D. Cubuk 18 60 0 20 Oct 2021
Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs A. Baidya Joel Dapello J. DiCarlo Tiago Marques AAML 25 6 0 20 Oct 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 273 0 28 Sep 2021
Neural Ensemble Search via Bayesian Sampling Yao Shu Yizhou Chen Zhongxiang Dai Bryan Kian Hsiang Low BDL 13 8 0 06 Sep 2021
Well-tuned Simple Nets Excel on Tabular Datasets Arlind Kadra Marius Lindauer Frank Hutter Josif Grabocka 15 185 0 21 Jun 2021
LENAS: Learning-based Neural Architecture Search and Ensemble for 3D Radiotherapy Dose Prediction Yi Lin Yanfei Liu Hao-tao Chen Xin Yang Kai Ma Yefeng Zheng Kwang-Ting Cheng 3DV 26 4 0 12 Jun 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles A. Tiulpin Matthew B. Blaschko UQCV FedML 31 4 0 29 May 2021
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search Arber Zela Julien N. Siems Frank Hutter 82 147 0 28 Jan 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 264 5,326 0 05 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015