NeurIPS Poster "uncertainty quantification" Papers
13 papers found
Conformal Linguistic Calibration: Trading-off between Factuality and Specificity
Zhengping Jiang, Anqi Liu, Ben Van Durme
NeurIPS 2025posterarXiv:2502.19110
7
citations
Contextual Thompson Sampling via Generation of Missing Data
Kelly W Zhang, Tianhui Cai, Hongseok Namkoong et al.
NeurIPS 2025posterarXiv:2502.07064
2
citations
Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
Xu Wan, Chao Yang, Cheng Yang et al.
NeurIPS 2025poster
Gaussian Approximation and Concentration of Constant Learning-Rate Stochastic Gradient Descent
Ziyang Wei, Jiaqi Li, Zhipeng Lou et al.
NeurIPS 2025poster
Infinite Neural Operators: Gaussian processes on functions
Daniel Augusto de Souza, Yuchen Zhu, Jake Cunningham et al.
NeurIPS 2025posterarXiv:2510.16675
1
citations
Knowledge Distillation of Uncertainty using Deep Latent Factor Model
Sehyun Park, Jongjin Lee, Yunseop Shin et al.
NeurIPS 2025posterarXiv:2510.19290
Neurosymbolic Diffusion Models
Emile van Krieken, Pasquale Minervini, Edoardo Maria Ponti et al.
NeurIPS 2025posterarXiv:2505.13138
3
citations
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation
Ting Wei, Biao Mei, Junliang Lyu et al.
NeurIPS 2025posterarXiv:2505.14161
1
citations
Probabilistic Reasoning with LLMs for Privacy Risk Estimation
Jonathan Zheng, Alan Ritter, Sauvik Das et al.
NeurIPS 2025poster
ProDAG: Projected Variational Inference for Directed Acyclic Graphs
Ryan Thompson, Edwin Bonilla, Robert Kohn
NeurIPS 2025posterarXiv:2405.15167
Statistical Inference for Gradient Boosting Regression
Haimo Fang, Kevin Tan, Giles Hooker
NeurIPS 2025posterarXiv:2509.23127
1
citations
Uncertainty Estimation by Flexible Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
NeurIPS 2025posterarXiv:2510.18322
Uncertainty Quantification with the Empirical Neural Tangent Kernel
Joseph Wilson, Chris van der Heide, Liam Hodgkinson et al.
NeurIPS 2025posterarXiv:2502.02870
5
citations