"uncertainty estimation" Papers

AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking

Soyoung Yoon, Gyuwan Kim, Gyu-Hwung Cho et al.

Causal Discovery via Bayesian Optimization

Bao Duong, Sunil Gupta, Thin Nguyen

Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification

Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.

Do LLMs estimate uncertainty well in instruction-following?

Juyeon Heo, Miao Xiong, Christina Heinze-Deml et al.

DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation

Maregu Assefa, Muzammal Naseer, IYYAKUTTI IYAPPAN GANAPATHI et al.

Enhancing Deep Batch Active Learning for Regression with Imperfect Data Guided Selection

Yinjie Min, Furong Xu, Xinyao Li et al.

Neural Context Flows for Meta-Learning of Dynamical Systems

Roussel Desmond Nzoyem, David Barton, Tom Deakin

Prior2Former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation

Sebastian Schmidt, Julius Koerner, Dominik Fuchsgruber et al.

Robust and Computation-Aware Gaussian Processes

SEGA: Shaping Semantic Geometry for Robust Hashing under Noisy Supervision

Yiyang Gu, Bohan Wu, Qinghua Ran et al.

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models

Haizhou Shi, Yibin Wang, Ligong Han et al.

Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data

Xingyu Ren, Pengwei Liu, Pengkai Wang et al.

Uncertainty-Sensitive Privileged Learning

Fan-Ming Luo, Lei Yuan, Yang Yu

Uncertainty Weighted Gradients for Model Calibration

Jinxu Lin, Linwei Tao, Minjing Dong et al.

Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling

Guillem Capellera, Antonio Rubio, Luis Ferraz et al.

A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models

Sebastian Gregor Gruber, Florian Buettner

An Empirical Study Into What Matters for Calibrating Vision-Language Models

Weijie Tu, Weijian Deng, Dylan Campbell et al.

cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Process

Yihang Chen, TSAI HOR CHAN, Guosheng Yin et al.

Conformalized Adaptive Forecasting of Heterogeneous Trajectories

Yanfei Zhou, Lars Lindemann, Matteo Sesia

Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts

Ha Manh Bui, Anqi Liu

Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution

Johannes Zenn, Robert Bamler

Efficient Exploration for LLMs

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao et al.

Enabling Uncertainty Estimation in Iterative Neural Networks

Nikita Durasov, Doruk Oner, Jonathan Donier et al.

Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification

Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.

Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation

JoonHo Lee, Jae Oh Woo, Juree Seok et al.

Learning Uncertainty-Aware Temporally-Extended Actions

Joongkyu Lee, Seung Joon Park, Yunhao Tang et al.

Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks

Yunfei Long, Zilin Tian, Liguo Zhang et al.

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes

Yingyi Chen, Qinghua Tao, Francesco Tonin et al.

SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets

Shenghua Wan, Ziyuan Chen, Le Gan et al.

Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting

Anthony Chen, Huanrui Yang, Yulu Gan et al.

Transitional Uncertainty with Layered Intermediate Predictions

Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib

Uncertainty Estimation by Density Aware Evidential Deep Learning

Taeseong Yoon, Heeyoung Kim

Variational Linearized Laplace Approximation for Bayesian Deep Learning

Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato

Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models

Authors: Jinqian Chen, Jihua Zhu, Qinghai Zheng et al.

Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation

Pei Liu, Luping Ji