https://github.com/nandantumu/conformal_region_designer
공식 코드Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates
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Conformal Prediction is a machine learning framework that provides valid measures of confidence for individual predictions. It offers a principled approach to quantify uncertainty in predictions without assuming any specific distribution for the data. This section features papers that explore various aspects of conformal prediction, including theoretical advancements, algorithmic developments, and applications across different domains.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates
CertDW: Towards Certified Dataset Ownership Verification via Conformal Prediction
Conformalized Deep Splines for Optimal and Efficient Prediction Sets
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
Conditional validity of heteroskedastic conformal regression
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals
Projected random forests and conformal prediction of circular data
Universal distribution of the empirical coverage in split conformal prediction
Marginal and training-conditional guarantees in one-shot federated conformal prediction
Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphs
Fundus Image-based Visual Acuity Assessment with PAC-Guarantees
Conformal Prediction for Dose-Response Models with Continuous Treatments
What If We Had Used a Different App? Reliable Counterfactual KPI Analysis in Wireless Systems
A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecasting
Inductive Conformal Prediction: A Straightforward Introduction with Examples in Python
Copula Conformal Prediction for Multi-step Time Series Forecasting
Adjusting Regression Models for Conditional Uncertainty Calibration
Distributionally Robust Predictive Runtime Verification under Spatio-Temporal Logic Specifications
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.