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covariance matrix

101 papers

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Co-occurring keywords

graphical model (864) covariance estimation (98) high-dimensional statistics (145) linear regression (282) conditional independence (113) gaussian graphical model (106) gaussian process (1200) riemannian geometry (68) principal component analysis (316) precision matrix (58)

Papers

Covariance Scattering Transforms AAAI 2026
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers JMLR 2025
Learning to Normalize on the SPD Manifold under Bures-Wasserstein Geometry CVPR 2025
A Correlation Manifold Self-Attention Network for EEG Decoding IJCAI 2025
A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening CVPR 2025
RiemStega: Covariance-Based Loss for Print-Proof Transmission of Data in Images WACV 2025
Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds JMLR 2025
Layered-Parameter Perturbation for Zeroth-Order Optimization of Optical Neural Networks AAAI 2025
Controllable Feature Whitening for Hyperparameter-Free Bias Mitigation ICCV 2025
Causal-Driven Skill Prerequisite Structure Discovery AAAI 2024
Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention NIPS 2024
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning NIPS 2024
Methods for recovering conditional independence graphs (Abstract Reprint) IJCAI 2024
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NIPS 2024
Better Batch for Deep Probabilistic Time Series Forecasting AISTATS 2024
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions NIPS 2023
Instrumental Processes Using Integrated Covariances CLEAR 2023
Semantic Similarity Covariance Matrix Shrinkage EMNLP 2023
Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph JMLR 2023
Feature Adaptation for Sparse Linear Regression NIPS 2023
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit NIPS 2023
Robust Linear Regression for General Feature Distribution AISTATS 2023
Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023
Learning Partial Correlation Based Deep Visual Representation for Image Classification CVPR 2023
On perfectness in Gaussian graphical models AISTATS 2022