ICML 2024 "uncertainty estimation" Papers
17 papers found
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
ICML 2024posterarXiv:2310.05833
An Empirical Study Into What Matters for Calibrating Vision-Language Models
Weijie Tu, Weijian Deng, Dylan Campbell et al.
ICML 2024posterarXiv:2402.07417
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
ICML 2024posterarXiv:2402.09623
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
Ha Manh Bui, Anqi Liu
ICML 2024posterarXiv:2302.06495
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution
Johannes Zenn, Robert Bamler
ICML 2024poster
Efficient Exploration for LLMs
Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao et al.
ICML 2024posterarXiv:2402.00396
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier et al.
ICML 2024posterarXiv:2403.16732
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
ICML 2024poster
Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation
JoonHo Lee, Jae Oh Woo, Juree Seok et al.
ICML 2024posterarXiv:2405.06424
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
ICML 2024poster
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
ICML 2024posterarXiv:2402.01476
SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets
Shenghua Wan, Ziyuan Chen, Le Gan et al.
ICML 2024posterarXiv:2406.09486
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan et al.
ICML 2024posterarXiv:2312.09148
Transitional Uncertainty with Layered Intermediate Predictions
Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib
ICML 2024posterarXiv:2405.17494
Uncertainty Estimation by Density Aware Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
ICML 2024posterarXiv:2409.08754
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
ICML 2024posterarXiv:2302.12565
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
Pei Liu, Luping Ji
ICML 2024posterarXiv:2405.04405