covariance matrix

Instrumental Processes Using Integrated Covariances CLeaR 2023 Learning Partial Correlation Based Deep Visual Representation for Image Classification CVPR 2023 Robust Linear Regression for General Feature Distribution AISTATS 2023 Semantic Similarity Covariance Matrix Shrinkage EMNLP 2023 Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023 The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions NeurIPS 2023 The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit NeurIPS 2023 Understanding the Covariance Structure of Convolutional Filters ICLR 2023 Conditional Linear Regression for Heterogeneous Covariances AISTATS 2022 coVariance Neural Networks NeurIPS 2022 Efficiency Ordering of Stochastic Gradient Descent NeurIPS 2022 Graphical Representations for Algebraic Constraints of Linear Structural Equations Models PGM 2022 Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification AAAI 2022 Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations JMLR 2022 On perfectness in Gaussian graphical models AISTATS 2022 Robust Streaming PCA NeurIPS 2022 Correlated Input-Dependent Label Noise in Large-Scale Image Classification CVPR 2021 Feature-Based SLAM: Why Simultaneous Localisation and Mapping? RSS 2021 Learning partial correlation graphs and graphical models by covariance queries JMLR 2021 On Feature Decorrelation in Self-Supervised Learning ICCV 2021 Online A-Optimal Design and Active Linear Regression ICML 2021 Sparse sketches with small inversion bias COLT 2021 The Sample Complexity of Robust Covariance Testing COLT 2021 A Finite-Sample Deviation Bound for Stable Autoregressive Processes L4DC 2020 Competing Speaker Count Estimation on the Fusion of the Spectral and Spatial Embedding Space Interspeech 2020