Copertina

Conformalized Gaussian processes for online uncertainty quantification over graphs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Jinwen, Lu, Qin, Giannakis, Georgios B.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Signal Processing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Low-Rank Adaptation Redux for Large Models
di: Li, Bingcong, et al.
Pubblicazione: (2026)

Online scalable Gaussian processes with conformal prediction for guaranteed coverage
di: Xu, Jinwen, et al.
Pubblicazione: (2024)

Topology Identification and Inference over Graphs
di: Mateos, Gonzalo, et al.
Pubblicazione: (2025)

Deploying AI for Signal Processing education: Selected challenges and intriguing opportunities
di: Haupt, Jarvis, et al.
Pubblicazione: (2025)

A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
di: Larsen, Kristoffer, et al.
Pubblicazione: (2023)

Conformal Inference for Time Series over Graphs
di: Dua, Sonakshi, et al.
Pubblicazione: (2025)

Learning From Crowdsourced Noisy Labels: A Signal Processing Perspective
di: Ibrahim, Shahana, et al.
Pubblicazione: (2024)

Efficient Gaussian process learning via subspace projections
di: Cazelles, Elsa, et al.
Pubblicazione: (2026)

Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
di: Kouw, Wouter M.
Pubblicazione: (2025)

Accelerated training of Gaussian processes using banded square exponential covariances
di: Ehrhardt, Emily C., et al.
Pubblicazione: (2026)

R2D2 image reconstruction with model uncertainty quantification in radio astronomy
di: Aghabiglou, Amir, et al.
Pubblicazione: (2024)

Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks
di: Bench, Ciaran, et al.
Pubblicazione: (2025)

Uncertainty quantification in neural network classifiers -- a local linear approach
di: Malmström, Magnus, et al.
Pubblicazione: (2023)

Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation
di: Orfanidis, Georgios I.
Pubblicazione: (2026)

Online Conformal Prediction with Corrupted Feedback
di: Wang, Bowen, et al.
Pubblicazione: (2026)

Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks
di: Zhang, Jinglin, et al.
Pubblicazione: (2020)

Mirror Online Conformal Prediction with Intermittent Feedback
di: Wang, Bowen, et al.
Pubblicazione: (2025)

Robust Bayesian Optimization via Localized Online Conformal Prediction
di: Kim, Dongwon, et al.
Pubblicazione: (2024)

Reliable Inference in Edge-Cloud Model Cascades via Conformal Alignment
di: Huang, Jiayi, et al.
Pubblicazione: (2025)

Collaborative Channel Access and Transmission for NR Sidelink and Wi-Fi Coexistence over Unlicensed Spectrum
di: Yan, Zhuangzhuang, et al.
Pubblicazione: (2025)

Comparative analysis and evaluation of ageing forecasting methods for semiconductor devices in online health monitoring
di: Villalobos, Adrian, et al.
Pubblicazione: (2025)

Distributed Learning of Quantum State Tomography Robust to Readout Errors
di: Taherpour, Amirhossein, et al.
Pubblicazione: (2026)

Bayesian uncertainty-aware deep learning with noisy labels: Tackling annotation ambiguity in EEG seizure detection
di: Shama, Deeksha M., et al.
Pubblicazione: (2024)

Spatially-Adaptive Conformal Graph Transformer for Indoor Localization in Wi-Fi Driven Networks
di: Lehyeh, Ayesh Abu, et al.
Pubblicazione: (2026)

InfoNCE Induces Gaussian Distribution
di: Betser, Roy, et al.
Pubblicazione: (2026)

EEG-SeeGraph: Interpreting functional connectivity disruptions in dementias via sparse-explanatory dynamic EEG-graph learning
di: Wu, Fengcheng, et al.
Pubblicazione: (2026)

On the Adversarial Robustness of Learning-based Conformal Novelty Detection
di: Zhang, Daofu, et al.
Pubblicazione: (2025)

Estimation of Food Intake Quantity Using Inertial Signals from Smartwatches
di: Levi, Ioannis, et al.
Pubblicazione: (2025)

Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition
di: Orfanidis, Georgios I., et al.
Pubblicazione: (2026)

On Generalization Bounds for Deep Compound Gaussian Neural Networks
di: Lyons, Carter, et al.
Pubblicazione: (2024)

Consensus-based Recursive Multi-Output Gaussian Process
di: Rao, Yogesh Prasanna Kumar, et al.
Pubblicazione: (2026)

Nonlinearity and Uncertainty Informed Moment-Matching Gaussian Mixture Splitting
di: Kulik, Jackson, et al.
Pubblicazione: (2024)

Surrogate modeling for Bayesian optimization beyond a single Gaussian process
di: Lu, Qin, et al.
Pubblicazione: (2022)

Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models
di: Wang, Jianhua, et al.
Pubblicazione: (2026)

Learning Context-conditioned Gaussian Overbounds for Convolution-Based Uncertainty Propagation
di: Liu, Ruirui, et al.
Pubblicazione: (2026)

Introducing Graph Learning over Polytopic Uncertain Graph
di: Kishida, Masako, et al.
Pubblicazione: (2024)

Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals
di: Buciulea, Andrei, et al.
Pubblicazione: (2024)

VSE: Variational state estimation of complex model-free process
di: Norén, Gustav, et al.
Pubblicazione: (2026)

Over-the-Air Inference over Multi-hop MIMO Networks
di: Bian, Chenghong, et al.
Pubblicazione: (2025)

CoVariance Filters and Neural Networks over Hilbert Spaces
di: Battiloro, Claudio, et al.
Pubblicazione: (2025)