ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1805.11327
  4. Cited By
Lightweight Probabilistic Deep Networks

Lightweight Probabilistic Deep Networks

29 May 2018
Jochen Gast
Stefan Roth
    UQCV
    OOD
    BDL
ArXivPDFHTML

Papers citing "Lightweight Probabilistic Deep Networks"

30 / 30 papers shown
Title
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
Abdullah Akgul
Manuel Haußmann
M. Kandemir
OffRL
66
1
0
17 Jan 2025
Delving into Differentially Private Transformer
Delving into Differentially Private Transformer
Youlong Ding
Xueyang Wu
Yining Meng
Yonggang Luo
Hao Wang
Weike Pan
29
5
0
28 May 2024
Uncertainty Quantification for Image-based Traffic Prediction across
  Cities
Uncertainty Quantification for Image-based Traffic Prediction across Cities
Alexander Timans
Nina Wiedemann
Nishant Kumar
Ye Hong
Martin Raubal
18
1
0
11 Aug 2023
Local and Global Information in Obstacle Detection on Railway Tracks
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
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation
S. Landgraf
Markus Hillemann
Kira Wursthorn
Markus Ulrich
SSeg
UQCV
26
6
0
19 Jul 2023
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step
  Inference
ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference
N. Durasov
Nik Dorndorf
Hieu M. Le
Pascal Fua
UQCV
25
10
0
21 Nov 2022
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for
  Autonomous Driving
SOTIF Entropy: Online SOTIF Risk Quantification and Mitigation for Autonomous Driving
Liang Peng
Boqi Li
Wen-Hui Yu
Kailiang Yang
Wenbo Shao
Hong Wang
AAML
28
24
0
08 Nov 2022
Quantifying Model Uncertainty for Semantic Segmentation using Operators
  in the RKHS
Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS
Rishabh Singh
José C. Príncipe
UQCV
28
3
0
03 Nov 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty
  in Graph Neural Networks
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks
Sai Munikoti
D. Agarwal
Laya Das
Balasubramaniam Natarajan
BDL
UD
31
13
0
20 May 2022
DXQ-Net: Differentiable LiDAR-Camera Extrinsic Calibration Using
  Quality-aware Flow
DXQ-Net: Differentiable LiDAR-Camera Extrinsic Calibration Using Quality-aware Flow
Xin Jing
X. Ding
R. Xiong
Huanjun Deng
Yue Wang
3DPC
19
24
0
17 Mar 2022
$Δ$-UQ: Accurate Uncertainty Quantification via Anchor
  Marginalization
ΔΔΔ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization
Rushil Anirudh
Jayaraman J. Thiagarajan
36
1
0
05 Oct 2021
$f$-Cal: Calibrated aleatoric uncertainty estimation from neural
  networks for robot perception
fff-Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception
Dhaivat Bhatt
Kaustubh Mani
Dishank Bansal
Krishna Murthy Jatavallabhula
Hanju Lee
Liam Paull
UQCV
23
5
0
28 Sep 2021
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal
  Estimation
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
Gwangbin Bae
Ignas Budvytis
R. Cipolla
29
113
0
20 Sep 2021
MotionHint: Self-Supervised Monocular Visual Odometry with Motion
  Constraints
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
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
32
1,109
0
07 Jul 2021
Shapley Explanation Networks
Shapley Explanation Networks
Rui Wang
Xiaoqian Wang
David I. Inouye
TDI
FAtt
19
44
0
06 Apr 2021
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Chao Qu
Wenxin Liu
Camillo J. Taylor
UQCV
BDL
19
31
0
29 Mar 2021
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware
  Regression
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
Bridging In- and Out-of-distribution Samples for Their Better
  Discriminability
Bridging In- and Out-of-distribution Samples for Their Better Discriminability
Engkarat Techapanurak
Anh-Chuong Dang
Takayuki Okatani
OODD
20
3
0
07 Jan 2021
Learning Accurate Dense Correspondences and When to Trust Them
Learning Accurate Dense Correspondences and When to Trust Them
Prune Truong
Martin Danelljan
Luc Van Gool
Radu Timofte
3DH
3DPC
68
128
0
05 Jan 2021
Accurate 3D Object Detection using Energy-Based Models
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
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
24
222
0
20 Nov 2020
Probabilistic Numeric Convolutional Neural Networks
Probabilistic Numeric Convolutional Neural Networks
Marc Finzi
Roberto Bondesan
Max Welling
BDL
AI4TS
23
13
0
21 Oct 2020
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
Alexander Shekhovtsov
V. Yanush
B. Flach
MQ
29
10
0
04 Jun 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDL
UQCV
31
277
0
24 Feb 2020
Dirichlet uncertainty wrappers for actionable algorithm accuracy
  accountability and auditability
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability
José Mena
O. Pujol
Jordi Vitrià
19
8
0
29 Dec 2019
A General Framework for Uncertainty Estimation in Deep Learning
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
Deep Active Learning with Adaptive Acquisition
Manuel Haussmann
Fred Hamprecht
M. Kandemir
16
41
0
27 Jun 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1