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. 2008.10546
  4. Cited By
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

24 August 2020
Lingkai Kong
Jimeng Sun
Chao Zhang
    UQCV
ArXivPDFHTML

Papers citing "SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates"

12 / 12 papers shown
Title
Universal Approximation Theorem of Deep Q-Networks
Universal Approximation Theorem of Deep Q-Networks
Qian Qi
20
1
0
04 May 2025
DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation
DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation
Xiaowei Mao
Yan Lin
S. Guo
Yubin Chen
Xingyu Xian
Haomin Wen
Qisen Xu
Youfang Lin
Huaiyu Wan
33
1
0
23 Aug 2024
Stable Neural Stochastic Differential Equations in Analyzing Irregular
  Time Series Data
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
YongKyung Oh
Dongyoung Lim
Sungil Kim
AI4TS
18
11
0
22 Feb 2024
Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware
  Predictions and Transfer Learning
Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning
Andrea Rossi
Andrea Visentin
Diego Carraro
Steven D. Prestwich
Kenneth N. Brown
14
0
0
24 Feb 2023
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
Bohan Tang
Yiqi Zhong
Chenxin Xu
Wei Wu
Ulrich Neumann
Yanfeng Wang
Ya-Qin Zhang
Siheng Chen
28
9
0
11 Jul 2022
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations
Jongwan Kim
Dongjin Lee
Byunggook Na
Seongsik Park
Jeonghee Jo
Sung-Hoon Yoon
19
0
0
15 Jun 2022
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Shiye Lei
Zhuozhuo Tu
Leszek Rutkowski
Feng Zhou
Li Shen
Fengxiang He
Dacheng Tao
BDL
8
2
0
12 Dec 2021
Climate Modeling with Neural Diffusion Equations
Climate Modeling with Neural Diffusion Equations
JeeHyun Hwang
Jeongwhan Choi
Hwan-Kyu Choi
Kookjin Lee
Dongeun Lee
Noseong Park
DiffM
11
22
0
11 Nov 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
20
61
0
25 Mar 2021
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
268
5,635
0
05 Dec 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
197
741
0
06 Jun 2015
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
247
9,042
0
06 Jun 2015
1