Didong Li | DeepAI

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Featured Co-authors

David B. Dunson
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Sudipto Banerjee
38 publications
Barbara E. Engelhardt
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Zhengwu Zhang
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Saptarshi Chakraborty
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Hengrui Luo
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Diana Cai
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∙ 05/20/2023

Contrastive inverse regression for dimension reduction

Supervised dimension reduction (SDR) has been a topic of growing interes...

0 Sam Hawke, et al. ∙

∙ 03/13/2023

Kernel Density Bayesian Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) is a powerful framework to infer an...

0 Aishwarya Mandyam, et al. ∙

∙ 11/01/2022

Tree Representations of Brain Structural Connectivity via Persistent Homology

The brain structural connectome is generated by a collection of white ma...

0 Didong Li, et al. ∙

∙ 04/23/2022

Spherical Rotation Dimension Reduction with Geometric Loss Functions

Modern datasets witness high-dimensionality and nontrivial geometries of...

0 Hengrui Luo, et al. ∙

∙ 10/15/2021

Multi-group Gaussian Processes

Gaussian processes (GPs) are pervasive in functional data analysis, mach...

0 Didong Li, et al. ∙

∙ 08/17/2021

From the Greene–Wu Convolution to Gradient Estimation over Riemannian Manifolds

Over a complete Riemannian manifold of finite dimension, Greene and Wu i...

0 Tianyu Wang, et al. ∙

∙ 04/08/2021

Fixed-Domain Inference for Gausian Processes with Matérn Covariogram on Compact Riemannian Manifolds

Gaussian processes are widely employed as versatile modeling and predict...

0 Didong Li, et al. ∙

∙ 02/12/2021

Contrastive latent variable modeling with application to case-control sequencing experiments

High-throughput RNA-sequencing (RNA-seq) technologies are powerful tools...

0 Andrew Jones, et al. ∙

∙ 12/14/2020

Probabilistic Contrastive Principal Component Analysis

Dimension reduction is useful for exploratory data analysis. In many app...

0 Didong Li, et al. ∙

∙ 09/04/2020

Density estimation and modeling on symmetric spaces

In many applications, data and/or parameters are supported on non-Euclid...

0 Didong Li, et al. ∙

∙ 08/17/2020

Principal Ellipsoid Analysis (PEA): Efficient non-linear dimension reduction clustering

Even with the rise in popularity of over-parameterized models, simple di...

71 Debolina Paul, et al. ∙

∙ 07/12/2019

Estimating densities with nonlinear support using Fisher-Gaussian kernels

Current tools for multivariate density estimation struggle when the dens...

0 Minerva Mukhopadhyay, et al. ∙

∙ 06/29/2019

Geodesic Distance Estimation with Spherelets

Many statistical and machine learning approaches rely on pairwise distan...

3 Didong Li, et al. ∙

∙ 05/26/2019

Efficient Curvature Estimation for Oriented Point Clouds

There is an immense literature focused on estimating the curvature of an...

0 Yueqi Cao, et al. ∙

∙ 03/03/2019

Classification via local manifold approximation

Classifiers label data as belonging to one of a set of groups based on i...

6 Didong Li, et al. ∙

∙ 06/26/2017

Efficient Manifold and Subspace Approximations with Spherelets

Data lying in a high-dimensional ambient space are commonly thought to h...

0 Didong Li, et al. ∙

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