"high-dimensional data" Papers

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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

Probabilistic Geometric Principal Component Analysis with application to neural data

Han-Lin Hsieh, Maryam Shanechi

ICLR 2025arXiv:2509.18469
3
citations

Proper Hölder-Kullback Dirichlet Diffusion: A Framework for High Dimensional Generative Modeling

Wanpeng Zhang, Yuhao Fang, Xihang Qiu et al.

NEURIPS 2025

QuanDA: Quantile-Based Discriminant Analysis for High-Dimensional Imbalanced Classification

Qian Tang, Yuwen Gu, Boxiang Wang

NEURIPS 2025

Better Locally Private Sparse Estimation Given Multiple Samples Per User

Yuheng Ma, Ke Jia, Hanfang Yang

ICML 2024arXiv:2408.04313
2
citations

Finite Smoothing Algorithm for High-Dimensional Support Vector Machines and Quantile Regression

Qian Tang, Yikai Zhang, Boxiang Wang

ICML 2024

Indirectly Parameterized Concrete Autoencoders

Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha et al.

ICML 2024arXiv:2403.00563
3
citations

Latent variable model for high-dimensional point process with structured missingness

Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki

ICML 2024arXiv:2402.05758
1
citations

Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference

Md Musfiqur Rahman, Murat Kocaoglu

ICML 2024arXiv:2401.01426
9
citations

Neural Auto-designer for Enhanced Quantum Kernels

Cong Lei, Yuxuan Du, Peng Mi et al.

ICLR 2024arXiv:2401.11098
9
citations