Lightweight Probabilistic Deep Networks

29 May 2018

Papers citing "Lightweight Probabilistic Deep Networks"

26 / 26 papers shown

Title
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning Abdullah Akgul Manuel Haußmann M. Kandemir OffRL 66 1 0 17 Jan 2025
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 16 1 0 11 Aug 2023
Local and Global Information in Obstacle Detection on Railway Tracks Matthias Brucker Andrei Cramariuc Cornelius von Einem Roland Siegwart César Cadena 22 8 0 28 Jul 2023
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation S. Landgraf Markus Hillemann Kira Wursthorn Markus Ulrich SSeg UQCV 19 6 0 19 Jul 2023
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference N. Durasov Nik Dorndorf Hieu M. Le Pascal Fua UQCV 18 10 0 21 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS Rishabh Singh José C. Príncipe UQCV 19 3 0 03 Nov 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks Sai Munikoti D. Agarwal Laya Das Balasubramaniam Natarajan BDL UD 18 13 0 20 May 2022
DXQ-Net: Differentiable LiDAR-Camera Extrinsic Calibration Using Quality-aware Flow Xin Jing X. Ding R. Xiong Huanjun Deng Yue Wang 3DPC 11 24 0 17 Mar 2022
$Δ$ -UQ: Accurate Uncertainty Quantification via Anchor Marginalization Rushil Anirudh Jayaraman J. Thiagarajan 26 1 0 05 Oct 2021
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation Gwangbin Bae Ignas Budvytis R. Cipolla 18 113 0 20 Sep 2021
MotionHint: Self-Supervised Monocular Visual Odometry with Motion Constraints Cong Wang Yu-Ping Wang Dinesh Manocha 21 9 0 14 Sep 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 30 1,108 0 07 Jul 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 17 44 0 06 Apr 2021
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty Chao Qu Wenxin Liu Camillo J. Taylor UQCV BDL 9 31 0 29 Mar 2021
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression Wanhua Li Xiaoke Huang Jiwen Lu Jianjiang Feng Jie Zhou UQCV 30 61 0 25 Mar 2021
Learning Accurate Dense Correspondences and When to Trust Them Prune Truong Martin Danelljan Luc Van Gool Radu Timofte 3DH 3DPC 66 128 0 05 Jan 2021
Accurate 3D Object Detection using Energy-Based Models Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon 3DPC 30 10 0 08 Dec 2020
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving Di Feng Ali Harakeh Steven Waslander Klaus C. J. Dietmayer AAML UQCV EDL 18 221 0 20 Nov 2020
Probabilistic Numeric Convolutional Neural Networks Marc Finzi Roberto Bondesan Max Welling BDL AI4TS 21 13 0 21 Oct 2020
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks Alexander Shekhovtsov V. Yanush B. Flach MQ 23 10 0 04 Jun 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 11 276 0 24 Feb 2020
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability José Mena O. Pujol Jordi Vitrià 11 8 0 29 Dec 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 31 289 0 16 Jul 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 14 41 0 27 Jun 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 252 9,134 0 06 Jun 2015