"maximum mean discrepancy" Papers

18 papers found

AlignMamba: Enhancing Multimodal Mamba with Local and Global Cross-modal Alignment

Yan Li, Yifei Xing, Xiangyuan Lan et al.

CVPR 2025arXiv:2412.00833
17
citations

Deep MMD Gradient Flow without adversarial training

Alexandre Galashov, Valentin De Bortoli, Arthur Gretton

ICLR 2025arXiv:2405.06780
10
citations

Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning

Yujing Wang, Hainan Zhang, Sijia Wen et al.

AAAI 2025paperarXiv:2406.14217
3
citations

Flowing Datasets with Wasserstein over Wasserstein Gradient Flows

Clément Bonet, Christophe Vauthier, Anna Korba

ICML 2025oralarXiv:2506.07534
7
citations

KAIROS: Scalable Model-Agnostic Data Valuation

Jiongli Zhu, Parjanya Prashant, Alex Cloninger et al.

NEURIPS 2025arXiv:2506.23799

Model Equality Testing: Which Model is this API Serving?

Irena Gao, Percy Liang, Carlos Guestrin

ICLR 2025arXiv:2410.20247
19
citations

PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models

Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo

ICLR 2025arXiv:2503.08085
3
citations

Rethinking Joint Maximum Mean Discrepancy for Visual Domain Adaptation

Wei Wang, Haifeng Xia, Chao Huang et al.

NEURIPS 2025oral
115
citations

A Distributional Analogue to the Successor Representation

Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.

ICML 2024spotlightarXiv:2402.08530
10
citations

Debiased Distribution Compression

Lingxiao Li, Raaz Dwivedi, Lester Mackey

ICML 2024arXiv:2404.12290
4
citations

Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning

Yuelin Zhang, Jiacheng Cen, Jiaqi Han et al.

ICML 2024

Kernel-Based Evaluation of Conditional Biological Sequence Models

Pierre Glaser, Steffan Paul, Alissa M. Hummer et al.

ICML 2024arXiv:2510.15601

M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy

Hansong Zhang, Shikun Li, Pengju Wang et al.

AAAI 2024paperarXiv:2312.15927
52
citations

MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy

Yan Sun, Jicong Fan

ICLR 2024spotlight

Privacy-Preserving Adaptive Re-Identification without Image Transfer

Hamza Rami, Jhony H. Giraldo, Nicolas Winckler et al.

ECCV 2024arXiv:2407.12589

Rethinking FID: Towards a Better Evaluation Metric for Image Generation

Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit et al.

CVPR 2024highlightarXiv:2401.09603
294
citations

Sample Complexity Bounds for Estimating Probability Divergences under Invariances

Behrooz Tahmasebi, Stefanie Jegelka

ICML 2024arXiv:2311.02868
11
citations

Submodular framework for structured-sparse optimal transport

Piyushi Manupriya, Pratik Kumar Jawanpuria, Karthik Gurumoorthy et al.

ICML 2024arXiv:2406.04914
1
citations