Yue Song

Orcid: 0000-0003-1573-5643

Affiliations:
  • University of Trento, Trento, Italy


According to our database1, Yue Song authored at least 32 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Kuramoto Orientation Diffusion Models.
CoRR, September, 2025

Langevin Flows for Modeling Neural Latent Dynamics.
CoRR, July, 2025

RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-Distribution Detection.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2025

Is CLIP ideal? No. Can we fix it? Yes!
CoRR, March, 2025

Gyrogroup Batch Normalization.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unsupervised Region-Based Image Editing of Denoising Diffusion Models.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Adaptive Log-Euclidean Metrics for SPD Matrix Learning.
IEEE Trans. Image Process., 2024

Unsupervised Representation Learning from Sparse Transformation Analysis.
CoRR, 2024

Product Geometries on Cholesky Manifolds with Applications to SPD Manifolds.
CoRR, 2024

RMLR: Extending Multinomial Logistic Regression into General Geometries.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Lie Group Approach to Riemannian Batch Normalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Riemannian Multinomial Logistics Regression for SPD Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Orthogonal SVD Covariance Conditioning and Latent Disentanglement.
IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Fast Differentiable Matrix Square Root and Inverse Square Root.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

On the Eigenvalues of Global Covariance Pooling for Fine-Grained Visual Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Disentangle Saliency Detection into Cascaded Detail Modeling and Body Filling.
ACM Trans. Multim. Comput. Commun. Appl., January, 2023

Flow Factorized Representation Learning.
CoRR, 2023

Riemannian Multiclass Logistics Regression for SPD Neural Networks.
CoRR, 2023

Latent Traversals in Generative Models as Potential Flows.
CoRR, 2023

Adaptive Riemannian Metrics on SPD Manifolds.
CoRR, 2023

Flow Factorized Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Latent Traversals in Generative Models as Potential Flows.
Proceedings of the International Conference on Machine Learning, 2023

Householder Projector for Unsupervised Latent Semantics Discovery.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Masked Jigsaw Puzzle: A Versatile Position Embedding for Vision Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Quasi-Equilibrium Feature Pyramid Network for Salient Object Detection.
IEEE Trans. Image Process., 2022

Breaking the Chain of Gradient Leakage in Vision Transformers.
CoRR, 2022

RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Differentiable Matrix Square Root.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality.
Proceedings of the Computer Vision, 2022

Batch-Efficient EigenDecomposition for Small and Medium Matrices.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021


  Loading...