ICML 2024 "manifold learning" Papers
7 papers found
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds
Jan Stanczuk, Georgios Batzolis, Teo Deveney et al.
ICML 2024poster
Disentanglement Learning via Topology
Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.
ICML 2024posterarXiv:2308.12696
Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics
Kaiping Zheng, Horng-Ruey Chua, Melanie Herschel et al.
ICML 2024poster
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
Jaehyeong Jo, Sung Ju Hwang
ICML 2024posterarXiv:2310.07216
Graph Geometry-Preserving Autoencoders
Jungbin Lim, Jihwan Kim, Yonghyeon Lee et al.
ICML 2024poster
Graph Mixup on Approximate Gromov–Wasserstein Geodesics
Zhichen Zeng, Ruizhong Qiu, Zhe Xu et al.
ICML 2024poster
Random matrix theory improved Fréchet mean of symmetric positive definite matrices
Florent Bouchard, Ammar Mian, Malik TIOMOKO et al.
ICML 2024posterarXiv:2405.06558