Cover Image

Effective Confidence Region Prediction Using Probability Forecasters

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lindsay, David, Lindsay, Sian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Transductive Confidence Machine and its application to Medical Data Sets
by: Lindsay, David
Published: (2024)

Learning from String Sequences
by: Lindsay, David, et al.
Published: (2024)

Temporal distribution of clusters of investors and their application in prediction with expert advice
by: Wisniewski, Wojciech, et al.
Published: (2024)

Confidence Under the Hood: An Investigation into the Confidence-Probability Alignment in Large Language Models
by: Kumar, Abhishek, et al.
Published: (2024)

COVID-19 Probability Prediction Using Machine Learning: An Infectious Approach
by: Ilani, Mohsen Asghari, et al.
Published: (2024)

Time Series Forecasting via Direct Per-Step Probability Distribution Modeling
by: Kong, Linghao, et al.
Published: (2025)

ALICE: An Interpretable Neural Architecture for Generalization in Substitution Ciphers
by: Shen, Jeff, et al.
Published: (2025)

Confidence-based Estimators for Predictive Performance in Model Monitoring
by: Kivimäki, Juhani, et al.
Published: (2024)

Conservative Prediction via Data-Driven Confidence Minimization
by: Choi, Caroline, et al.
Published: (2023)

CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee
by: Yang, Chao, et al.
Published: (2025)

Are Self-Attentions Effective for Time Series Forecasting?
by: Kim, Dongbin, et al.
Published: (2024)

Are KANs Effective for Multivariate Time Series Forecasting?
by: Han, Xiao, et al.
Published: (2024)

Skillful Kilometer-Scale Regional Weather Forecasting via Global and Regional Coupling
by: Chen, Weiqi, et al.
Published: (2026)

It's Not You, It's Clipping: A Soft Trust-Region via Probability Smoothing for LLM RL
by: Dwyer, Madeleine, et al.
Published: (2025)

Accurately Predicting Probabilities of Safety-Critical Rare Events for Intelligent Systems
by: Bai, Ruoxuan, et al.
Published: (2024)

Generalising Traffic Forecasting to Regions without Traffic Observations
by: Su, Xinyu, et al.
Published: (2025)

A Latent Space Metric for Enhancing Prediction Confidence in Earth Observation Data
by: Pitsiorlas, Ioannis, et al.
Published: (2024)

Trust, or Don't Predict: Introducing the CWSA Family for Confidence-Aware Model Evaluation
by: Shahnazari, Kourosh, et al.
Published: (2025)

Flowing with Confidence
by: de Kruiff, Friso, et al.
Published: (2026)

Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation
by: Chang, Trenton, et al.
Published: (2024)

KANFormer for Predicting Fill Probabilities via Survival Analysis in Limit Order Books
by: Zhong, Jinfeng, et al.
Published: (2025)

STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting
by: Zhao, Zhengyang, et al.
Published: (2024)

TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
by: Taga, Ege Onur, et al.
Published: (2025)

A Cost-Effective Framework for Predicting Parking Availability Using Geospatial Data and Machine Learning
by: Bagosher, Madyan, et al.
Published: (2025)

Confident Feature Ranking
by: Neuhof, Bitya, et al.
Published: (2023)

Probably Approximately Correct Maximum A Posteriori Inference
by: Shorvon, Matthew, et al.
Published: (2026)

BandPO: Bridging Trust Regions and Ratio Clipping via Probability-Aware Bounds for LLM Reinforcement Learning
by: Li, Yuan, et al.
Published: (2026)

Towards a Practical Understanding of Lagrangian Methods in Safe Reinforcement Learning
by: Spoor, Lindsay, et al.
Published: (2025)

Towards Effective Fusion and Forecasting of Multimodal Spatio-temporal Data for Smart Mobility
by: Wang, Chenxing
Published: (2024)

PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
by: Niu, Yiming, et al.
Published: (2025)

Bridging Internal Probability and Self-Consistency for Effective and Efficient LLM Reasoning
by: Zhou, Zhi, et al.
Published: (2025)

Best of mini-N in-loop Sampling: A Contextual Quality Reward Model for Reliable and Efficient Best-of-N Sampling
by: Rho, Hyung Gyu, et al.
Published: (2025)

Conformal Prediction for Time-series Forecasting with Change Points
by: Sun, Sophia, et al.
Published: (2025)

Confidence Optimization for Probabilistic Encoding
by: Xia, Pengjiu, et al.
Published: (2025)

DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
by: Ao, Xiang, et al.
Published: (2026)

KVSculpt: KV Cache Compression as Distillation
by: Jiang, Bo, et al.
Published: (2026)

Confidence Interval Estimation of Predictive Performance in the Context of AutoML
by: Paraschakis, Konstantinos, et al.
Published: (2024)

COSMOS: Predictable and Cost-Effective Adaptation of LLMs
by: Wang, Jiayu, et al.
Published: (2025)

Beyond Confidence: Rethinking Self-Assessments for Performance Prediction in LLMs
by: Bhattacharyya, Sree, et al.
Published: (2026)

Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction
by: Xue, Yuan, et al.
Published: (2024)