Didong Li

Orcid: 0000-0001-9146-705X

According to our database1, Didong Li authored at least 17 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Spherical Rotation Dimension Reduction with Geometric Loss Functions.
J. Mach. Learn. Res., 2024

Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning?
CoRR, 2024

STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics.
CoRR, 2024

Lower Ricci Curvature for Efficient Community Detection.
CoRR, 2024

2023
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds.
J. Mach. Learn. Res., 2023

Contrastive inverse regression for dimension reduction.
CoRR, 2023

Kernel Density Bayesian Inverse Reinforcement Learning.
CoRR, 2023

On the Identifiability and Interpretability of Gaussian Process Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Exponential-Wrapped Distributions on Symmetric Spaces.
SIAM J. Math. Data Sci., December, 2022

Spherical Rotation Dimension Reduction with Geometric Loss Functions.
CoRR, 2022

2021
Efficient Weingarten map and curvature estimation on manifolds.
Mach. Learn., 2021

From the Greene-Wu Convolution to Gradient Estimation over Riemannian Manifolds.
CoRR, 2021

2020
A Geometric Approach to Average Problems on Multinomial and Negative Multinomial Models.
Entropy, 2020

Probabilistic Contrastive Principal Component Analysis.
CoRR, 2020

2019
Efficient Curvature Estimation for Oriented Point Clouds.
CoRR, 2019

Classification via local manifold approximation.
CoRR, 2019

2017
A Geodesic-Based Riemannian Gradient Approach to Averaging on the Lorentz Group.
Entropy, 2017


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