Enabling Uncertainty Estimation in Iterative Neural Networks
Not on the map. Why?
Abstract (arXiv)
Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of their successive outputs is highly correlated with the accuracy of the value to which they converge. Thus, we can use the convergence rate as a useful proxy for uncertainty. This results in an approach to uncertainty estimation that provides state-of-the-art estimates at a much lower computational cost than techniques like Ensembles, and without requiring any modifications to the original iterative model. We demonstrate its practical value by embedding it in two application domains: road detection in aerial images and the estimation of aerodynamic properties of 2D and 3D shapes.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 46 of its 85 references that are in the map. First posted on arXiv 25 Mar 2024.
Builds on
46 of 85 references.
References · 46
- 2017Attention Is All You Needcited by 59,932
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2017On Calibration of Modern Neural Networkscited by 4,860
- 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,416
- 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,888
- 2018Neural Ordinary Differential Equationscited by 3,733
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
- 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
- 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
- 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
- 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,483
- 2015Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)cited by 1,061
34 more
- 2016Stacked Hourglass Networks for Human Pose Estimationcited by 913
- 2018Predictive Uncertainty Estimation via Prior Networkscited by 555
- 2015Variational Dropout and the Local Reparameterization Trickcited by 489
- 2016Geometric deep learning on graphs and manifolds using mixture model CNNscited by 468
- 2019Deep Ensembles: A Loss Landscape Perspectivecited by 438
- 2020BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learningcited by 368
- 2015Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networkscited by 295
- 2021Exploring the Limits of Out-of-Distribution Detectioncited by 283
- 2018PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsingcited by 224
- 2020Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learningcited by 208
- 2019Topology-Preserving Deep Image Segmentationcited by 198
- 2019Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Visioncited by 182
- 2015Human Pose Estimation with Iterative Error Feedbackcited by 121
- 2013Generalized Denoising Auto-Encoders as Generative Modelscited by 113
- 2020MeshSDF: Differentiable Iso-Surface Extractioncited by 112
- 2018RoadTracer: Automatic Extraction of Road Networks from Aerial Imagescited by 102
- 2020Masksembles for Uncertainty Estimationcited by 88
- 2020Bayesian Deep Learning via Subnetwork Inferencecited by 85
- 2017Beyond the Pixel-Wise Loss for Topology-Aware Delineationcited by 82
- 2019Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagationcited by 74
- 2017On weight initialization in deep neural networkscited by 67
- 2020Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic Flowscited by 60
- 2022Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detectioncited by 59
- 2020Depth Uncertainty in Neural Networkscited by 56
- 2017Improving the Expected Improvement Algorithmcited by 54
- 2018Geodesic Convolutional Shape Optimizationcited by 37
- 2019Recurrent U-Net for Resource-Constrained Segmentationcited by 27
- 2021Deep Deterministic Uncertainty for Semantic Segmentationcited by 24
- 2020Promoting Connectivity of Network-Like Structures by Enforcing Region Separationcited by 19
- 2022ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inferencecited by 15
- 2018Double Refinement Network for Efficient Indoor Monocular Depth Estimationcited by 5
- 2017Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detectioncited by 4
- 2022PartAL: Efficient Partial Active Learning in Multi-Task Visual Settingscited by 3
- 2021Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineatecited by 1
Built on by
Citing papers per year: 2024: 7; 2025: 3; 2026: 1.
11 papers.
- 2024MirrorCheck: Efficient Adversarial Defense for Vision-Language Modelscited by 19
- 2024Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifiercited by 12
- 2024Assessing Sample Quality via the Latent Space of Generative Modelscited by 8
- 2024IT3: Idempotent Test-Time Trainingcited by 6
- 2024Shadow Removal Refinement via Material-Consistent Shadow Edgescited by 5
- 2024Uncertainty Estimation for 3D Object Detection via Evidential Learningcited by 5
- 2024Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentationcited by 2
- 2025High Resolution UDF Meshing via Iterative Networkscited by 2
- 2025CORA: Consistency-Guided Semi-Supervised Framework for Reasoning Segmentationcited by 1
- 2025C(NN)FD -- Deep Learning Modelling of Multi-Stage Axial Compressors Aerodynamicscited by 0
- 2026Uncertainty Quantification in Federated Granger Causality Learningcited by 0
- 2026Uncertainty Quantification in Federated Granger Causality Learning13 Feb 2026
- 2025CORA: Consistency-Guided Semi-Supervised Framework for Reasoning Segmentation21 Nov 2025
- 2025High Resolution UDF Meshing via Iterative Networks21 Sep 2025
- 2025C(NN)FD -- Deep Learning Modelling of Multi-Stage Axial Compressors Aerodynamics18 Mar 2025
- 2024Uncertainty Estimation for 3D Object Detection via Evidential Learning31 Oct 2024
- 2024IT3: Idempotent Test-Time Training5 Oct 2024
- 2024Shadow Removal Refinement via Material-Consistent Shadow Edges10 Sep 2024
- 2024Assessing Sample Quality via the Latent Space of Generative Models21 Jul 2024
- 2024Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation17 Jul 2024
- 2024Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier4 Jul 2024
- 2024MirrorCheck: Efficient Adversarial Defense for Vision-Language Models13 Jun 2024