Lan-Zhe Guo

About Lan-Zhe Guo

Lan-Zhe Guo, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Nanjing University, specializes in the field of Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

LAMDA-SSL: a comprehensive semi-supervised learning toolkit

Offline Imitation Learning without Auxiliary High-quality Behavior Data

A Benchmark on Robust Semi-Supervised Learning in Open Environments

Investigating the limitation of clip models: The worst-performing categories

DualMatch: Robust Semi-supervised Learning with Dual-Level Interaction

ODS: test-time adaptation in the presence of open-world data shift

Bidirectional adaptation for robust semi-supervised learning with inconsistent data distributions

Identifying Useful Learnwares for Heterogeneous Label Spaces

Lan-Zhe Guo Information

University

Position

___

Citations(all)

597

Citations(since 2020)

592

Cited By

78

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

11

i10Index(since 2020)

11

Email

University Profile Page

Google Scholar

Lan-Zhe Guo Skills & Research Interests

Machine Learning

Top articles of Lan-Zhe Guo

LAMDA-SSL: a comprehensive semi-supervised learning toolkit

2024/1

Offline Imitation Learning without Auxiliary High-quality Behavior Data

2023/10/13

A Benchmark on Robust Semi-Supervised Learning in Open Environments

2023/10/13

Investigating the limitation of clip models: The worst-performing categories

arXiv preprint arXiv:2310.03324

2023/10/5

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Yu-Feng Li
Yu-Feng Li

H-Index: 23

DualMatch: Robust Semi-supervised Learning with Dual-Level Interaction

2023/9/18

ODS: test-time adaptation in the presence of open-world data shift

2023/7/3

Bidirectional adaptation for robust semi-supervised learning with inconsistent data distributions

2023/7/3

Identifying Useful Learnwares for Heterogeneous Label Spaces

2023/4/24

Interactive reweighting for mitigating label quality issues

IEEE Transactions on Visualization and Computer Graphics

2023/12/21

Examining the Achilles' Heel of CLIP Models: The Worst-Performing Categories

2023/10/13

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Yu-Feng Li
Yu-Feng Li

H-Index: 23

You Only Submit One Image to Find the Most Suitable Generative Model

2023/10/13

Log: Active model adaptation for label-efficient ood generalization

Advances in Neural Information Processing Systems

2022/12/6

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Yu-Feng Li
Yu-Feng Li

H-Index: 23

Robust semi-supervised learning when not all classes have labels

Advances in Neural Information Processing Systems

2022/12/6

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Yu-Feng Li
Yu-Feng Li

H-Index: 23

Transfer and share: semi-supervised learning from long-tailed data

Machine Learning

2022/10/31

Tong Wei
Tong Wei

H-Index: 4

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Open-set learning under covariate shift

Machine Learning

2022/10/27

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

LAMDA-SSL: Semi-supervised learning in python

arXiv preprint arXiv:2208.04610

2022/8/9

Class-imbalanced semi-supervised learning with adaptive thresholding

2022/6/28

Lan-Zhe Guo
Lan-Zhe Guo

H-Index: 4

Yu-Feng Li
Yu-Feng Li

H-Index: 23

Robust deep semi-supervised learning: A brief introduction

arXiv preprint arXiv:2202.05975

2022/2/12

Step: Out-of-distribution detection in the presence of limited in-distribution labeled data

Advances in Neural Information Processing Systems

2021/12/6

See List of Professors in Lan-Zhe Guo University(Nanjing University)

Co-Authors

academic-engine