Depth Uncertainty in Neural Networks

15 June 2020

Javier Antorán

J. Allingham

José Miguel Hernández-Lobato

Papers citing "Depth Uncertainty in Neural Networks"

50 / 58 papers shown

Title
Generative Uncertainty in Diffusion Models Metod Jazbec Eliot Wong-Toi Guoxuan Xia Dan Zhang Eric T. Nalisnick Stephan Mandt DiffM 43 0 0 28 Feb 2025
Uncertainty Estimation for 3D Object Detection via Evidential Learning N. Durasov Rafid Mahmood Jiwoong Choi Marc T. Law James Lucas Pascal Fua Jose M. Alvarez UQCV EDL 3DPC 47 1 0 31 Oct 2024
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling Yury Gorishniy Akim Kotelnikov Artem Babenko LMTD MoE 85 6 0 31 Oct 2024
Improved Depth Estimation of Bayesian Neural Networks Bart Van Erp Bert De Vries MDE BDL 24 0 0 14 Oct 2024
Gaussian Mixture based Evidential Learning for Stereo Matching Weide Liu Xingxing Wang Lu Wang Jun Cheng Fayao Liu Xulei Yang 26 0 0 05 Aug 2024
To Believe or Not to Believe Your LLM Yasin Abbasi-Yadkori Ilja Kuzborskij András György Csaba Szepesvári UQCV 53 40 0 04 Jun 2024
Transitional Uncertainty with Layered Intermediate Predictions Ryan Benkert M. Prabhushankar Ghassan AlRegib 24 1 0 25 May 2024
Error-Driven Uncertainty Aware Training Pedro Mendes Paolo Romano David Garlan UQCV 24 0 0 02 May 2024
Fast Ensembling with Diffusion Schrödinger Bridge Hyunsu Kim Jongmin Yoon Juho Lee FedML UQCV 16 1 0 24 Apr 2024
QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles N. Ghanathe Steve Wilton UQCV 19 0 0 19 Apr 2024
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning Xudong Yu Chenjia Bai Hongyi Guo Changhong Wang Zhen Wang OffRL 32 0 0 09 Apr 2024
Lightweight Inference for Forward-Forward Algorithm Amin Aminifar Baichuan Huang Azra Abtahi Amir Aminifar 23 3 0 08 Apr 2024
Enabling Uncertainty Estimation in Iterative Neural Networks N. Durasov Doruk Öner Jonathan Donier Hieu M. Le Pascal Fua UQCV 38 8 0 25 Mar 2024
DeepCover: Advancing RNN Test Coverage and Online Error Prediction using State Machine Extraction Pouria Golshanrad Fathiyeh Faghih 12 5 0 10 Feb 2024
SAE: Single Architecture Ensemble Neural Networks Martin Ferianc Hongxiang Fan Miguel R. D. Rodrigues UQCV 8 0 0 09 Feb 2024
Early-Exit Neural Networks with Nested Prediction Sets Metod Jazbec Patrick Forré Stephan Mandt Dan Zhang Eric T. Nalisnick UQCV 16 1 0 10 Nov 2023
Learning Layer-wise Equivariances Automatically using Gradients Tycho F. A. van der Ouderaa Alexander Immer Mark van der Wilk MLT 36 12 0 09 Oct 2023
DebSDF: Delving into the Details and Bias of Neural Indoor Scene Reconstruction Yuting Xiao Jingwei Xu Zehao Yu Shenghua Gao 29 12 0 29 Aug 2023
Integrating Large Pre-trained Models into Multimodal Named Entity Recognition with Evidential Fusion Weide Liu Xiaoyang Zhong Jingwen Hou Shaohua Li Haozhe Huang Yuming Fang EDL 22 5 0 29 Jun 2023
Traversing Between Modes in Function Space for Fast Ensembling Eunggu Yun Hyungi Lee G. Nam Juho Lee UQCV 24 2 0 20 Jun 2023
Deep Active Learning with Structured Neural Depth Search Xiaoyun Zhang Xieyi Ping Jianwei Zhang 32 0 0 05 Jun 2023
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity Metod Jazbec J. Allingham Dan Zhang Eric T. Nalisnick 11 11 0 05 Jun 2023
FineMorphs: Affine-diffeomorphic sequences for regression Michele Lohr L. Younes 21 0 0 26 May 2023
Reweighted Mixup for Subpopulation Shift Zongbo Han Zhipeng Liang Fan Yang Liu Liu Lanqing Li ... P. Zhao Qinghua Hu Bing Wu Changqing Zhang Jianhua Yao 24 3 0 09 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 11 0 0 06 Apr 2023
Probabilistic Circuits That Know What They Don't Know Fabrizio G. Ventola Steven Braun Zhongjie Yu Martin Mundt Kristian Kersting UQCV TPM 11 7 0 13 Feb 2023
Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization Neslihan Kose R. Krishnan Akash Dhamasia Omesh Tickoo Michael Paulitsch 17 1 0 09 Dec 2022
Sampling-based inference for large linear models, with application to linearised Laplace Javier Antorán Shreyas Padhy Riccardo Barbano Eric T. Nalisnick David Janz José Miguel Hernández-Lobato BDL 27 17 0 10 Oct 2022
Variational Inference for Infinitely Deep Neural Networks Achille Nazaret David M. Blei BDL 23 11 0 21 Sep 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup Zongbo Han Zhipeng Liang Fan Yang Liu Liu Lanqing Li Yatao Bian P. Zhao Bing Wu Changqing Zhang Jianhua Yao 48 34 0 19 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 25 4 0 17 Sep 2022
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior Riccardo Barbano Johannes Leuschner Javier Antorán Bangti Jin José Miguel Hernández-Lobato 19 12 0 11 Jul 2022
Ensembling over Classifiers: a Bias-Variance Perspective Neha Gupta Jamie Smith Ben Adlam Zelda E. Mariet FedML UQCV FaML 11 6 0 21 Jun 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 25 28 0 17 Jun 2022
Trusted Multi-View Classification with Dynamic Evidential Fusion Zongbo Han Changqing Zhang H. Fu Joey Tianyi Zhou EDL 15 216 0 25 Apr 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 22 10 0 28 Feb 2022
Improving robustness and calibration in ensembles with diversity regularization H. A. Mehrtens Camila González Anirban Mukhopadhyay UQCV 9 7 0 26 Jan 2022
Latent Time Neural Ordinary Differential Equations Srinivas Anumasa P. K. Srijith BDL 14 5 0 23 Dec 2021
Addressing Bias in Active Learning with Depth Uncertainty Networks... or Not Chelsea Murray J. Allingham Javier Antorán José Miguel Hernández-Lobato AI4CE 14 4 0 13 Dec 2021
Depth Uncertainty Networks for Active Learning Chelsea Murray J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV AI4CE 20 2 0 13 Dec 2021
Model-Value Inconsistency as a Signal for Epistemic Uncertainty Angelos Filos Eszter Vértes Zita Marinho Gregory Farquhar Diana Borsa A. Friesen Feryal M. P. Behbahani Tom Schaul André Barreto Simon Osindero 44 7 0 08 Dec 2021
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions Huan Ma Zongbo Han Changqing Zhang H. Fu Joey Tianyi Zhou Q. Hu EDL UQCV 66 42 0 11 Nov 2021
Toward Accurate and Reliable Iris Segmentation Using Uncertainty Learning Jianze Wei Huaibo Huang Muyi Sun Yunlong Wang Min Ren R. He Zhenan Sun 23 2 0 20 Oct 2021
Sparse MoEs meet Efficient Ensembles J. Allingham F. Wenzel Zelda E. Mariet Basil Mustafa J. Puigcerver ... Balaji Lakshminarayanan Jasper Snoek Dustin Tran Carlos Riquelme Ruiz Rodolphe Jenatton MoE 44 21 0 07 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 26 11 0 06 Oct 2021
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks Zhilu Zhang Vianne R. Gao M. Sabuncu UQCV 19 6 0 09 Jun 2021
Can a single neuron learn predictive uncertainty? Edgardo Solano-Carrillo UQCV 21 1 0 07 Jun 2021
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness Namuk Park S. Kim UQCV AAML 11 19 0 26 May 2021
Improving Uncertainty Calibration via Prior Augmented Data Jeffrey Willette Juho Lee Sung Ju Hwang UQCV 11 0 0 22 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 200 81 0 16 Feb 2021