SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

24 August 2020

Lingkai Kong

Jimeng Sun

Chao Zhang

UQCV

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

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Title
Universal Approximation Theorem of Deep Q-Networks Qian Qi 30 1 0 04 May 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 42 0 0 12 Jan 2025
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 39 1 0 23 Aug 2024
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data YongKyung Oh Dongyoung Lim Sungil Kim AI4TS 43 11 0 22 Feb 2024
Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning Andrea Rossi Andrea Visentin Diego Carraro Steven D. Prestwich Kenneth N. Brown 25 0 0 24 Feb 2023
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent Richard Archibald F. Bao Yanzhao Cao Hui‐Jie Sun 43 2 0 17 Dec 2022
End-to-End Stochastic Optimization with Energy-Based Model Lingkai Kong Jiaming Cui Yuchen Zhuang Rui Feng B. Prakash Chao Zhang 13 16 0 25 Nov 2022
The Neural Process Family: Survey, Applications and Perspectives Saurav Jha Dong Gong Xuesong Wang Richard E. Turner L. Yao BDL 73 24 0 01 Sep 2022
Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics Zhengyang Zhou Yang Kuo Wei Sun Binwu Wang Mingxing Zhou Yunan Zong Yang Wang AI4TS 24 3 0 17 Aug 2022
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 36 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 29 0 0 15 Jun 2022
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 23 2 0 12 Dec 2021
Climate Modeling with Neural Diffusion Equations JeeHyun Hwang Jeongwhan Choi Hwan-Kyu Choi Kookjin Lee Dongeun Lee Noseong Park DiffM 19 22 0 11 Nov 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 24 60 0 27 May 2021
Accurate and Reliable Forecasting using Stochastic Differential Equations Peng Cui Zhijie Deng Wenbo Hu Jun Zhu UQCV 28 1 0 28 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
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li D. Duvenaud BDL UQCV 21 46 0 12 Feb 2021
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference Jiyang Xie Zhanyu Ma Jing-Hao Xue Guoqiang Zhang Jun Guo BDL 19 11 0 17 Nov 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015