https://github.com/gitvicky/spatio-temporal-uq
공식 코드Uncertainty Quantification of Surrogate Models using Conformal Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
Uncertainty Quantification of Surrogate Models using Conformal Prediction
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Target Strangeness: A Novel Conformal Prediction Difficulty Estimator
Spatial-Aware Conformal Prediction for Trustworthy Hyperspectral Image Classification
Conformal prediction for text infilling and part-of-speech prediction
Similarity-Navigated Conformal Prediction for Graph Neural Networks
WaveCatBoost for Probabilistic Forecasting of Regional Air Quality Data
Large language model validity via enhanced conformal prediction methods
libconform v0.1.0: a Python library for conformal prediction
A novel Deep Learning approach for one-step Conformal Prediction approximation
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction
CICLe: Conformal In-Context Learning for Largescale Multi-Class Food Risk Classification
Non-Exchangeable Conformal Language Generation with Nearest Neighbors
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data
Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction
Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction
Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning
Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.