"epistemic uncertainty" Papers
22 papers found
Conference
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
Yifan Lin, Enlu Zhou
Architectural and Inferential Inductive Biases for Exchangeable Sequence Modeling
Daksh Mittal, Leon Li, Thomson Yen et al.
Enhancing Vision-Language Model Reliability with Uncertainty-Guided Dropout Decoding
Yixiong Fang, Ziran Yang, Zhaorun Chen et al.
Epistemic Uncertainty for Generated Image Detection
Jun Nie, Yonggang Zhang, Tongliang Liu et al.
Evidential Knowledge Distillation
Liangyu Xiang, Junyu Gao, Changsheng Xu
From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation
Nikita Kotelevskii, Vladimir Kondratyev, Martin Takáč et al.
General Uncertainty Estimation with Delta Variances
Simon Schmitt, John Shawe-Taylor, Hado van Hasselt
On Rollouts in Model-Based Reinforcement Learning
Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow et al.
Rethinking Approximate Gaussian Inference in Classification
Bálint Mucsányi, Nathaël Da Costa, Philipp Hennig
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
Variational Uncertainty Decomposition for In-Context Learning
I. Shavindra Jayasekera, Jacob Si, Filippo Valdettaro et al.
Vicinal Label Supervision for Reliable Aleatoric and Epistemic Uncertainty Estimation
Linye Li, Yufei Chen, Xiaodong Yue
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou, Yujian Liu, Kaizhi Qian et al.
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
Xuanlong Yu, Gianni Franchi, Jindong Gu et al.
Distinguishing the Knowable from the Unknowable with Language Models
Gustaf Ahdritz, Tian Qin, Nikhil Vyas et al.
Dynamic Knowledge Injection for AIXI Agents
Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks
Hanjing Wang, Qiang Ji
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
Luca Franco, Paolo Mandica, Konstantinos Kallidromitis et al.
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
Mira Juergens, Nis Meinert, Viktor Bengs et al.
One Step Closer to Unbiased Aleatoric Uncertainty Estimation
Wang Zhang, Ziwen Martin Ma, Subhro Das et al.
PAGER: Accurate Failure Characterization in Deep Regression Models
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi et al.