On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks

17 March 2022

Papers citing "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks"

22 / 22 papers shown

Title
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties Jiaxiang Yi Miguel A. Bessa UD PER UQCV 46 0 0 05 May 2025
OccuEMBED: Occupancy Extraction Merged with Building Energy Disaggregation for Occupant-Responsive Operation at Scale Yufei Zhang Andrew Sonta 29 0 0 23 Apr 2025
C-DiffSET: Leveraging Latent Diffusion for SAR-to-EO Image Translation with Confidence-Guided Reliable Object Generation Jeonghyeok Do Jaehyup Lee Munchurl Kim DiffM 48 1 0 16 Nov 2024
Deep Modeling of Non-Gaussian Aleatoric Uncertainty Aastha Acharya Caleb Lee Marissa DÁlonzo Jared Shamwell Nisar R. Ahmed Rebecca L. Russell BDL 46 0 0 30 May 2024
Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images Jadie Adams Krithika S. Iyer Shireen Elhabian 27 2 0 15 May 2024
Probabilistic Forecasting of Irregular Time Series via Conditional Flows Vijaya Krishna Yalavarthi Randolf Scholz Stefan Born Lars Schmidt-Thieme AI4TS 35 0 0 09 Feb 2024
Identifying Drivers of Predictive Aleatoric Uncertainty Pascal Iversen Simon Witzke Katharina Baum Bernhard Y. Renard UD 53 1 0 12 Dec 2023
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty Anshul Nayak A. Eskandarian Zachary R. Doerzaph P. Ghorai 35 4 0 26 May 2023
Coherent Soft Imitation Learning Joe Watson Sandy H. Huang Nicholas Heess 32 11 0 25 May 2023
Integrating Uncertainty into Neural Network-based Speech Enhancement Hu Fang Dennis Becker S. Wermter Timo Gerkmann UQCV 29 2 0 15 May 2023
UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time Series Patrick Ebel Vivien Sainte Fare Garnot M. Schmitt Jan Dirk Wegner Xiao Xiang Zhu 20 32 0 11 Apr 2023
Inductive biases in deep learning models for weather prediction Jannik Thümmel Matthias Karlbauer S. Otte C. Zarfl Georg Martius ... Thomas Scholten Ulrich Friedrich V. Wulfmeyer B. Goswami Martin Volker Butz AI4CE 43 5 0 06 Apr 2023
Faithful Heteroscedastic Regression with Neural Networks Andrew Stirn H. Wessels Megan D. Schertzer L. Pereira Neville E. Sanjana David A. Knowles UQCV 25 14 0 18 Dec 2022
Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting Seongjin Choi Nicolas Saunier Vincent Zhihao Zheng M. Trépanier Lijun Sun 16 1 0 10 Dec 2022
Estimating Regression Predictive Distributions with Sample Networks Ali Harakeh Jordan S. K. Hu Naiqing Guan Steven L. Waslander Liam Paull BDL UQCV 22 4 0 24 Nov 2022
Autoinverse: Uncertainty Aware Inversion of Neural Networks Navid Ansari Hans-Peter Seidel Nima Vahidi Ferdowsi Vahid Babaei BDL 16 12 0 29 Aug 2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger Luigi Gresele Jack Brady Julius von Kügelgen Dominik Zietlow Bernhard Schölkopf Georg Martius Wieland Brendel M. Besserve DRL 35 19 0 06 Jun 2022
Developing hierarchical anticipations via neural network-based event segmentation Christian Gumbsch M. Adam B. Elsner Georg Martius Martin Volker Butz 21 5 0 04 Jun 2022
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement Matias Valdenegro-Toro Daniel Saromo UD PER BDL UQCV 16 76 0 20 Apr 2022
Autoencoder-based background reconstruction and foreground segmentation with background noise estimation Bruno Sauvalle A. de La Fortelle 21 12 0 15 Dec 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015