"manifold learning" Papers

15 papers found

Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding

Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin et al.

CVPR 2025arXiv:2503.18010
3
citations

Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models

Louis Bethune, David Vigouroux, Yilun Du et al.

NEURIPS 2025arXiv:2505.18230
2
citations

Manifold Learning by Mixture Models of VAEs for Inverse Problems

Giovanni S. Alberti, Johannes Hertrich, Matteo Santacesaria et al.

ICLR 2025arXiv:2303.15244
12
citations

Multivariate Time Series Anomaly Detection with Idempotent Reconstruction

Xin Sun, Heng Zhou, Chao Li

NEURIPS 2025

Random Forest Autoencoders for Guided Representation Learning

Adrien Aumon, Shuang Ni, Myriam Lizotte et al.

NEURIPS 2025arXiv:2502.13257
5
citations

The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction

Alex Kokot, Octavian-Vlad Murad, Marina Meila

ICML 2025
2
citations

Toward a Unified Geometry Understanding : Riemannian Diffusion Framework for Graph Generation and Prediction

Yisen Gao, Xingcheng Fu, Qingyun Sun et al.

NEURIPS 2025arXiv:2510.04522

Diffusion Models Encode the Intrinsic Dimension of Data Manifolds

Jan Stanczuk, Georgios Batzolis, Teo Deveney et al.

ICML 2024

Disentanglement Learning via Topology

Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.

ICML 2024arXiv:2308.12696
3
citations

DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition

Sijie Wang, Rui She, Qiyu Kang et al.

AAAI 2024paperarXiv:2312.10616
11
citations

Exploiting Negative Samples: A Catalyst for Cohort Discovery in Healthcare Analytics

Kaiping Zheng, Horng-Ruey Chua, Melanie Herschel et al.

ICML 2024

Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes

Jaehyeong Jo, Sung Ju Hwang

ICML 2024arXiv:2310.07216
16
citations

Graph Geometry-Preserving Autoencoders

Jungbin Lim, Jihwan Kim, Yonghyeon Lee et al.

ICML 2024

Graph Mixup on Approximate Gromov–Wasserstein Geodesics

Zhichen Zeng, Ruizhong Qiu, Zhe Xu et al.

ICML 2024

Random matrix theory improved Fréchet mean of symmetric positive definite matrices

Florent Bouchard, Ammar Mian, Malik TIOMOKO et al.

ICML 2024arXiv:2405.06558
1
citations