Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling? - Yue Song 002; Nicu Sebe; Wei Wang 108 (ICCV, 2021)

Batch-Efficient EigenDecomposition for Small and Medium Matrices. - Yue Song 002; Nicu Sebe; Wei Wang 108 (ECCV (23), 2022)

Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality. - Yue Song 002; Nicu Sebe; Wei Wang 108 (ECCV (24), 2022)

Fast Differentiable Matrix Square Root. - Yue Song 002; Nicu Sebe; Wei Wang 108 (ICLR, 2022)

RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection. - Yue Song 002; Nicu Sebe; Wei Wang 108 (NeurIPS, 2022)

Breaking the Chain of Gradient Leakage in Vision Transformers. - Yahui Liu; Bin Ren 005; Yue Song 002; Wei Bi; Nicu Sebe; Wei Wang 108 (CoRR, 2022)

Quasi-Equilibrium Feature Pyramid Network for Salient Object Detection. - Yue Song 002; Hao Tang 005; Mengyi Zhao; Nicu Sebe; Wei Wang 108 (IEEE Trans. Image Process., 2022)

Masked Jigsaw Puzzle: A Versatile Position Embedding for Vision Transformers. - Bin Ren 005; Yahui Liu; Yue Song 002; Wei Bi; Rita Cucchiara; Nicu Sebe; Wei Wang 108 (CVPR, 2023)

Householder Projector for Unsupervised Latent Semantics Discovery. - Yue Song 002; Jichao Zhang; Nicu Sebe; Wei Wang 108 (ICCV, 2023)

Latent Traversals in Generative Models as Potential Flows. - Yue Song 002; T. Anderson Keller 001; Nicu Sebe; Max Welling (ICML, 2023)

Flow Factorized Representation Learning. - Yue Song 002; Andy Keller; Nicu Sebe; Max Welling (NeurIPS, 2023)

Adaptive Riemannian Metrics on SPD Manifolds. - Ziheng Chen 001; Tianyang Xu; Zhiwu Huang; Yue Song 002; Xiao-Jun Wu 001; Nicu Sebe (CoRR, 2023)

Latent Traversals in Generative Models as Potential Flows. - Yue Song 002; Andy Keller; Nicu Sebe; Max Welling (CoRR, 2023)

Riemannian Multiclass Logistics Regression for SPD Neural Networks. - Ziheng Chen 001; Yue Song 002; Gaowen Liu; Ramana Rao Kompella; Xiaojun Wu 001; Nicu Sebe (CoRR, 2023)

Flow Factorized Representation Learning. - Yue Song 002; T. Anderson Keller 001; Nicu Sebe; Max Welling (CoRR, 2023)

Disentangle Saliency Detection into Cascaded Detail Modeling and Body Filling. - Yue Song 002; Hao Tang 005; Nicu Sebe; Wei Wang 108 (ACM Trans. Multim. Comput. Commun. Appl., 2023)

On the Eigenvalues of Global Covariance Pooling for Fine-Grained Visual Recognition. - Yue Song 002; Nicu Sebe; Wei Wang 108 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Fast Differentiable Matrix Square Root and Inverse Square Root. - Yue Song 002; Nicu Sebe; Wei Wang 108 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Orthogonal SVD Covariance Conditioning and Latent Disentanglement. - Yue Song 002; Nicu Sebe; Wei Wang 108 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Riemannian Multinomial Logistics Regression for SPD Neural Networks. - Ziheng Chen 001; Yue Song 002; Gaowen Liu; Ramana Rao Kompella; Xiao-Jun Wu 001; Nicu Sebe (CVPR, 2024)

A Lie Group Approach to Riemannian Batch Normalization. - Ziheng Chen 001; Yue Song 002; Yunmei Liu; Nicu Sebe (ICLR, 2024)

RMLR: Extending Multinomial Logistic Regression into General Geometries. - Ziheng Chen 001; Yue Song 002; Rui Wang 050; Xiaojun Wu 001; Nicu Sebe (NeurIPS, 2024)

Product Geometries on Cholesky Manifolds with Applications to SPD Manifolds. - Ziheng Chen 001; Yue Song 002; Xiao-Jun Wu 001; Nicu Sebe (CoRR, 2024)

Unsupervised Representation Learning from Sparse Transformation Analysis. - Yue Song 002; T. Anderson Keller 001; Yisong Yue; Pietro Perona; Max Welling (CoRR, 2024)

Adaptive Log-Euclidean Metrics for SPD Matrix Learning. - Ziheng Chen 001; Yue Song 002; Tianyang Xu; Zhiwu Huang; Xiaojun Wu 001; Nicu Sebe (IEEE Trans. Image Process., 2024)

Unsupervised Region-Based Image Editing of Denoising Diffusion Models. - Zixiang Li; Yue Song 002; Renshuai Tao; Xiaohong Jia 002; Yao Zhao 001; Wei Wang 108 (AAAI, 2025)

Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry. - Ziheng Chen 001; Yue Song 002; Xiaojun Wu 001; Gaowen Liu; Nicu Sebe (ICLR, 2025)

Gyrogroup Batch Normalization. - Ziheng Chen 001; Yue Song 002; Xiaojun Wu 001; Nicu Sebe (ICLR, 2025)

Is CLIP ideal? No. Can we fix it? Yes! - Raphi Kang; Yue Song 002; Georgia Gkioxari; Pietro Perona (CoRR, 2025)

RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-Distribution Detection. - Yue Song 002; Wei Wang 108; Nicu Sebe (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Langevin Flows for Modeling Neural Latent Dynamics. - Yue Song 002; T. Anderson Keller 001; Yisong Yue; Pietro Perona; Max Welling (CoRR, 2025)

Kuramoto Orientation Diffusion Models. - Yue Song 002; T. Anderson Keller 001; Sevan Brodjian; Takeru Miyato; Yisong Yue; Pietro Perona; Max Welling (CoRR, 2025)