Hyperparameter Ensembles for Robustness and Uncertainty Quantification

24 June 2020

Papers citing "Hyperparameter Ensembles for Robustness and Uncertainty Quantification"

50 / 134 papers shown

Title
Classifier Ensemble for Efficient Uncertainty Calibration of Deep Neural Networks for Image Classification Michael Schulze Nikolas Ebert Laurenz Reichardt Oliver Wasenmüller UQCV 42 0 0 20 Jan 2025
Stein Variational Newton Neural Network Ensembles Klemens Flöge Mohammed Abdul Moeed Vincent Fortuin BDL UQCV 37 0 0 04 Nov 2024
Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling Guiyu Zhang Huan-ang Gao Zijian Jiang Hao Zhao Zhedong Zheng EGVM 46 6 0 15 Oct 2024
Boosting Deep Ensembles with Learning Rate Tuning Hongpeng Jin Yanzhao Wu 21 0 0 10 Oct 2024
Dynamic Post-Hoc Neural Ensemblers Sebastian Pineda Arango Maciej Janowski Lennart Purucker Arber Zela Frank Hutter Josif Grabocka UQCV 36 0 0 06 Oct 2024
LiRA: Light-Robust Adversary for Model-based Reinforcement Learning in Real World Taisuke Kobayashi 68 2 0 29 Sep 2024
Scalable Ensemble Diversification for OOD Generalization and Detection Alexander Rubinstein Luca Scimeca Damien Teney Seong Joon Oh BDL OOD 353 1 0 25 Sep 2024
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology Mario De Florio Zongren Zou Daniele E. Schiavazzi George Karniadakis 26 3 0 13 Aug 2024
Low-Cost Self-Ensembles Based on Multi-Branch Transformation and Grouped Convolution Hojung Lee Jong-Seok Lee 3DV 35 1 0 05 Aug 2024
Network Fission Ensembles for Low-Cost Self-Ensembles Hojung Lee Jong-Seok Lee UQCV 54 0 0 05 Aug 2024
LoRA-Ensemble: Efficient Uncertainty Modelling for Self-attention Networks Michelle Halbheer Dominik J. Mühlematter Alexander Becker Dominik Narnhofer Helge Aasen Konrad Schindler Mehmet Özgür Türkoglu UQCV 30 1 0 23 May 2024
Application of Deep Learning Methods to Processing of Noisy Medical Video Data Danil Afonchikov E. Kornaeva Irina Makovik Alexey Kornaev 23 0 0 16 Apr 2024
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning Xudong Yu Chenjia Bai Hongyi Guo Changhong Wang Zhen Wang OffRL 37 0 0 09 Apr 2024
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers Anh-Vu Bui Vy Vo Tung Pham Dinh Q. Phung Trung Le FedML UQCV 29 1 0 19 Mar 2024
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution Tailin Wu W. Neiswanger Hongtao Zheng Stefano Ermon J. Leskovec AI4CE 11 3 0 13 Feb 2024
SAE: Single Architecture Ensemble Neural Networks Martin Ferianc Hongxiang Fan Miguel R. D. Rodrigues UQCV 10 0 0 09 Feb 2024
How Good is a Single Basin? Kai Lion Lorenzo Noci Thomas Hofmann Gregor Bachmann UQCV 23 2 0 05 Feb 2024
Inadequacy of common stochastic neural networks for reliable clinical decision support Adrian Lindenmeyer Malte Blattmann S. Franke Thomas Neumuth Daniel Schneider BDL 25 1 0 24 Jan 2024
On Task Performance and Model Calibration with Supervised and Self-Ensembled In-Context Learning Chengzu Li Han Zhou Goran Glavavs Anna Korhonen Ivan Vulić 19 11 0 21 Dec 2023
Learning to Compose SuperWeights for Neural Parameter Allocation Search Piotr Teterwak Soren Nelson Nikoli Dryden D. Bashkirova Kate Saenko Bryan A. Plummer 25 1 0 03 Dec 2023
Uncertainty Quantification in Neural-Network Based Pain Intensity Estimation Burcu Ozek Zhenyuan Lu S. Radhakrishnan S. Kamarthi 20 2 0 14 Nov 2023
A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Shigang Chen Ronald Fick Miles Medina Christine Angelini 10 16 0 08 Nov 2023
Sensitivity-Aware Amortized Bayesian Inference Lasse Elsemüller Hans Olischläger Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 23 7 0 17 Oct 2023
United We Stand: Using Epoch-wise Agreement of Ensembles to Combat Overfit Uri Stern Daniel Shwartz D. Weinshall 33 1 0 17 Oct 2023
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data Konstantinos Pitas Julyan Arbel BDL UQCV FedML 29 0 0 04 Oct 2023
Deterministic Langevin Unconstrained Optimization with Normalizing Flows James M. Sullivan U. Seljak 24 0 0 01 Oct 2023
LoRA ensembles for large language model fine-tuning Xi Wang Laurence Aitchison Maja Rudolph UQCV 23 33 0 29 Sep 2023
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks Piyush Tiwary Atri Guha Subhodip Panda Prathosh A.P. MU GAN 55 7 0 25 Sep 2023
Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorance Lei Fan Bo Liu Haoxiang Li Ying Wu Gang Hua 14 4 0 14 Sep 2023
Multiclass Alignment of Confidence and Certainty for Network Calibration Vinith Kugathasan M. H. Khan UQCV 14 1 0 06 Sep 2023
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
Likelihood-ratio-based confidence intervals for neural networks Laurens Sluijterman Eric Cator Tom Heskes UQCV 30 0 0 04 Aug 2023
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation Jung Hyun Ryu Jaeheyoung Jeon Jewoong Cho Myung-joo Kang MoMe 11 1 0 05 Jul 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 21 9 0 20 Jun 2023
Multiclass Confidence and Localization Calibration for Object Detection Bimsara Pathiraja Malitha Gunawardhana M. H. Khan UQCV 34 15 0 14 Jun 2023
Synthetic data, real errors: how (not) to publish and use synthetic data B. V. Breugel Zhaozhi Qian M. Schaar SyDa 57 28 0 16 May 2023
Image retrieval outperforms diffusion models on data augmentation Max F. Burg F. Wenzel Dominik Zietlow Max Horn Osama Makansi Francesco Locatello Chris Russell VLM DiffM 37 16 0 20 Apr 2023
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning Hanjing Wang D. Joshi Shiqiang Wang Q. Ji UQCV BDL 14 6 0 10 Apr 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis OOD UQCV 14 2 0 08 Apr 2023
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification Meng Wang Tian Lin Lianyu Wang Aidi Lin K. Zou ... Y. Liu C. Pang Xinjian Chen Haoyu Chen H. Fu 82 35 0 08 Apr 2023
A Survey of Historical Learning: Learning Models with Learning History Xiang Li Ge Wu Lingfeng Yang Wenzhe Wang Renjie Song Jian Yang MU AI4TS 23 2 0 23 Mar 2023
Bayesian Quadrature for Neural Ensemble Search Saad Hamid Xingchen Wan Martin Jørgensen Binxin Ru Michael A. Osborne BDL UQCV 28 1 0 15 Mar 2023
Deep incremental learning models for financial temporal tabular datasets with distribution shifts Thomas Wong Mauricio Barahona OOD AIFin AI4TS 18 0 0 14 Mar 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries Charlotte Loh Seung-Jun Han Shivchander Sudalairaj Rumen Dangovski Kai Xu F. Wenzel Marin Soljacic Akash Srivastava UQCV 39 1 0 04 Mar 2023
Toward Robust Uncertainty Estimation with Random Activation Functions Y. Stoyanova Soroush Ghandi M. Tavakol UQCV 13 2 0 28 Feb 2023
A Survey on Uncertainty Quantification Methods for Deep Learning Wenchong He Zhe Jiang Tingsong Xiao Zelin Xu Yukun Li BDL UQCV AI4CE 19 18 0 26 Feb 2023
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play J. Liu Krishnamurthy Dvijotham Jihyeon Janel Lee Quan Yuan Martin Strobel Balaji Lakshminarayanan Deepak Ramachandran 21 5 0 11 Feb 2023
Confidence-based Reliable Learning under Dual Noises Peng Cui Yang Yue Zhijie Deng Jun Zhu NoLa 31 8 0 10 Feb 2023
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications Chengyu Dong OOD UQCV BDL AI4CE 24 0 0 02 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 38 13 0 01 Feb 2023