Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

17 June 2020

Balaji Lakshminarayanan

UQCV

BDL

ArXiv PDF HTML

Papers citing "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness"

50 / 296 papers shown

Title
Effective Data Selection for Seismic Interpretation through Disagreement Ryan Benkert Mohit Prabhushankar Ghassan AlRegib 37 2 0 01 Jun 2024
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning Fahimeh Fakour Ali Mosleh Ramin Ramezani UQCV UD PER 43 1 0 01 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 62 1 0 31 May 2024
Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities Alexander Nikitin Jannik Kossen Yarin Gal Pekka Marttinen UQCV 53 23 0 30 May 2024
When and How Does In-Distribution Label Help Out-of-Distribution Detection? Xuefeng Du Yiyou Sun Yixuan Li 37 7 0 28 May 2024
Confidence-aware multi-modality learning for eye disease screening K. Zou Tian Lin Zongbo Han Meng Wang Xuedong Yuan Haoyu Chen Changqing Zhang Xiaojing Shen Huazhu Fu 61 3 0 28 May 2024
Transitional Uncertainty with Layered Intermediate Predictions Ryan Benkert Mohit Prabhushankar Ghassan AlRegib 48 1 0 25 May 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification Kaizheng Wang Fabio Cuzzolin Keivan K1 Shariatmadar David Moens Hans Hallez UQCV BDL 85 6 0 23 May 2024
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling Shifan Zhao Jiaying Lu Carl Yang Edmond Chow Yuanzhe Xi 44 1 0 22 May 2024
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation Pei Liu Luping Ji EDL 29 4 0 07 May 2024
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification Hai-Vy Nguyen Fabrice Gamboa Reda Chhaibi Sixin Zhang Serge Gratton Thierry Giaccone FedML UQCV 23 0 0 12 Apr 2024
Efficient Training of Probabilistic Neural Networks for Survival Analysis Christian Marius Lillelund Martin Magris Christian Fischer Pedersen 28 3 0 09 Apr 2024
Kermut: Composite kernel regression for protein variant effects Peter Mørch Groth Mads Herbert Kerrn Lars Olsen Jesper Salomon Wouter Boomsma 42 2 0 09 Apr 2024
Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation M. Dreissig Florian Piewak Joschka Boedecker 35 1 0 09 Apr 2024
MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation Taha Koleilat Hojat Asgariandehkordi H. Rivaz Yiming Xiao VLM MedIm 50 9 0 29 Mar 2024
Informed Spectral Normalized Gaussian Processes for Trajectory Prediction Christian Schlauch Christian Wirth Nadja Klein 29 1 0 18 Mar 2024
Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts H. Bui Anqi Liu OOD BDL UQCV 46 4 0 07 Mar 2024
A prediction rigidity formalism for low-cost uncertainties in trained neural networks Filippo Bigi Sanggyu Chong Michele Ceriotti Federico Grasselli 52 5 0 04 Mar 2024
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks Bálint Mucsányi Michael Kirchhof Seong Joon Oh UQCV BDL OODD 431 20 1 29 Feb 2024
Mitigating Distributional Shift in Semantic Segmentation via Uncertainty Estimation from Unlabelled Data David S. W. Williams Daniele De Martini Matthew Gadd Paul Newman UQCV 29 5 0 27 Feb 2024
Masked Gamma-SSL: Learning Uncertainty Estimation via Masked Image Modeling David S. W. Williams Matthew Gadd Paul Newman Daniele De Martini UQCV 22 1 0 27 Feb 2024
Pretrained Visual Uncertainties Michael Kirchhof Mark Collier Seong Joon Oh Enkelejda Kasneci UQCV 410 8 1 26 Feb 2024
Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods Jiaxin Zhang Kamalika Das Kumar Sricharan UQCV 35 0 0 20 Feb 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 37 3 0 16 Feb 2024
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation S. Landgraf Markus Hillemann Theodor Kapler Markus Ulrich UQCV 26 8 0 16 Feb 2024
Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection Genki Osada Tsubasa Takahashi Takashi Nishide OODD 6 1 0 16 Feb 2024
UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers Hong Jia Young D. Kwon Dong Ma Nhat Pham Lorena Qendro Tam N. Vu Cecilia Mascolo 27 2 0 14 Feb 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 83 7 0 12 Feb 2024
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs He Zhao V. Kitsios Terry O'Kane Edwin V. Bonilla CML 24 1 0 06 Feb 2024
How Does Unlabeled Data Provably Help Out-of-Distribution Detection? Xuefeng Du Zhen Fang Ilias Diakonikolas Yixuan Li OODD 43 27 0 05 Feb 2024
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes Yingyi Chen Qinghua Tao F. Tonin Johan A. K. Suykens 22 1 0 02 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 36 5 0 02 Feb 2024
Inadequacy of common stochastic neural networks for reliable clinical decision support Adrian Lindenmeyer Malte Blattmann S. Franke Thomas Neumuth Daniel Schneider BDL 35 1 0 24 Jan 2024
Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study Yufei Li Simin Chen Yanghong Guo Wei Yang Yue Dong Cong Liu UQCV 25 1 0 12 Jan 2024
Wasserstein Distance-based Expansion of Low-Density Latent Regions for Unknown Class Detection Prakash Mallick Feras Dayoub Jamie Sherrah 19 1 0 10 Jan 2024
Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation Melrose Roderick Felix Berkenkamp Fatemeh Sheikholeslami Zico Kolter UQCV 16 0 0 29 Dec 2023
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 32 82 0 14 Dec 2023
Thermodynamic Computing System for AI Applications Denis Melanson M. A. Khater Maxwell Aifer Kaelan Donatella Max Hunter Gordon Thomas Dybdahl Ahle Gavin Crooks Antonio J. Martinez Faris M. Sbahi Patrick J. Coles AI4CE 23 6 0 08 Dec 2023
Transferable Candidate Proposal with Bounded Uncertainty Kyeongryeol Go Kye-Hyeon Kim 31 0 0 07 Dec 2023
Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission Jianfeng He Linlin Yu Shuo Lei Chang-Tien Lu Feng Chen UQLM 20 8 0 15 Nov 2023
Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi Sepp Hochreiter 28 11 0 14 Nov 2023
Improvements on Uncertainty Quantification for Node Classification via Distance-Based Regularization Russell Hart Linlin Yu Yifei Lou Feng Chen UQCV 20 4 0 10 Nov 2023
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks Jiarong Xu Renhong Huang Xin Jiang Yuxuan Cao Carl Yang Chunping Wang Yang Yang AI4CE 31 14 0 02 Nov 2023
Uncertainty quantification and out-of-distribution detection using surjective normalizing flows Simon Dirmeier Ye Hong Yanan Xin Fernando Pérez-Cruz UQCV 28 1 0 01 Nov 2023
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods Ling Huang S. Ruan Yucheng Xing Mengling Feng 41 20 0 09 Oct 2023
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness Fran Jelenić Josip Jukić Martin Tutek Mate Puljiz Jan vSnajder OODD 26 5 0 04 Oct 2023
Uncertainty Aware Deep Learning for Particle Accelerators Kishansingh Rajput Malachi Schram Karthik Somayaji 17 2 0 25 Sep 2023
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications John S. Schreck D. Gagne Charlie Becker William E. Chapman K. Elmore ... Vanessa M. Pryzbylo Jacob T. Radford B. Saavedra Justin Willson Christopher D. Wirz BDL UD OOD UQCV EDL 13 8 0 22 Sep 2023
LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition Haoxuan Qu Xiaofei Hui Yujun Cai Jun Liu 49 10 0 22 Sep 2023
PAGER: A Framework for Failure Analysis of Deep Regression Models Jayaraman J. Thiagarajan V. Narayanaswamy Puja Trivedi Rushil Anirudh 33 0 0 20 Sep 2023