Cover Image

Be Bayesian by Attachments to Catch More Uncertainty

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shen, Shiyu, Pan, Bin, Shi, Tianyang, Li, Tao, Shi, Zhenwei
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Domain Generalization Guided by Large-Scale Pre-Trained Priors
by: Wang, Zongbin, et al.
Published: (2024)

A Pretrained Probabilistic Transformer for City-Scale Traffic Volume Prediction
by: Shen, Shiyu, et al.
Published: (2025)

Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework
by: Li, Junxian, et al.
Published: (2024)

Uncertainty-aware Traffic Prediction under Missing Data
by: Mei, Hao, et al.
Published: (2023)

Dual-Branched Spatio-temporal Fusion Network for Multi-horizon Tropical Cyclone Track Forecast
by: Liu, Zili, et al.
Published: (2022)

Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
by: Yang, Rui, et al.
Published: (2024)

Less is More: on the Over-Globalizing Problem in Graph Transformers
by: Xing, Yujie, et al.
Published: (2024)

Wonderful Matrices: More Efficient and Effective Architecture for Language Modeling Tasks
by: Shi, Jingze, et al.
Published: (2024)

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)

Tackling Fake Forgetting through Uncertainty Quantification
by: Shi, Yingdan, et al.
Published: (2025)

Learning More with Less: A Dynamic Dual-Level Down-Sampling Framework for Efficient Policy Optimization
by: Wang, Chao, et al.
Published: (2025)

Adaptive Defense against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler
by: Hu, Zixuan, et al.
Published: (2025)

Bayesian-Symbolic Integration for Uncertainty-Aware Parking Prediction
by: Nezhadettehad, Alireza, et al.
Published: (2026)

Wonderful Matrices: Combining for a More Efficient and Effective Foundation Model Architecture
by: Shi, Jingze, et al.
Published: (2024)

WSSM: Geographic-enhanced hierarchical state-space model for global station weather forecast
by: Yang, Songru, et al.
Published: (2025)

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024)

Fairness in Survival Analysis: A Novel Conditional Mutual Information Augmentation Approach
by: Xie, Tianyang, et al.
Published: (2025)

OLMA: One Loss for More Accurate Time Series Forecasting
by: Shi, Tianyi, et al.
Published: (2025)

Reinforcement Learning with Curriculum-inspired Adaptive Direct Policy Guidance for Truck Dispatching
by: Meng, Shi, et al.
Published: (2025)

vLinear: A Powerful Linear Model for Multivariate Time Series Forecasting
by: Yue, Wenzhen, et al.
Published: (2026)

Exploring Neural Ordinary Differential Equations as Interpretable Healthcare classifiers
by: Li, Shi
Published: (2025)

More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration
by: Yuan, Xiaoyang, et al.
Published: (2025)

Beyond Feature Fusion: Contextual Bayesian PEFT for Multimodal Uncertainty Estimation
by: Naderi, Habibeh, et al.
Published: (2026)

Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing
by: Abdennadher, Yesmine, et al.
Published: (2026)

Uncertainty Quantification of Large Language Models using Approximate Bayesian Computation
by: Sharma, Mridul, et al.
Published: (2025)

Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
by: Ruhe, David, et al.
Published: (2019)

Factor Decorrelation Enhanced Data Removal from Deep Predictive Models
by: Yang, Wenhao, et al.
Published: (2025)

Catching a Moving Subspace: Low-Rank Bandits Beyond Stationarity
by: Khosravi, Hamed, et al.
Published: (2026)

Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization
by: Wang, Zihan, et al.
Published: (2025)

Preserving Domain Generalization in Fine-Tuning via Joint Parameter Selection
by: Pan, Bin, et al.
Published: (2025)

LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation
by: Guo, Ke, et al.
Published: (2024)

More Bang for the Buck: Process Reward Modeling with Entropy-Driven Uncertainty
by: Cao, Lang, et al.
Published: (2025)

Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification
by: Rodemann, Julian, et al.
Published: (2026)

Cross-Modal Bayesian Low-Rank Adaptation for Uncertainty-Aware Multimodal Learning
by: Naderi, Habibeh, et al.
Published: (2026)

Enhancing Uncertainty Estimation and Interpretability via Bayesian Non-negative Decision Layer
by: Hu, Xinyue, et al.
Published: (2025)

From Black-box to Causal-box: Towards Building More Interpretable Models
by: Hwang, Inwoo, et al.
Published: (2025)

Modeling and Performance Analysis for Semantic Communications Based on Empirical Results
by: Ma, Shuai, et al.
Published: (2025)

Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation
by: Zhu, Jiaqi, et al.
Published: (2026)

CleverCatch: A Knowledge-Guided Weak Supervision Model for Fraud Detection
by: Mozafari, Amirhossein, et al.
Published: (2025)

Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting
by: Wang, Yijun, et al.
Published: (2026)