Product
Help
Pricing
About
Jobs
Log in
Get started
Author
Add to collection
ChengAo Shen
Observed names:
Chengao Shen,
Shen, ChengAo
Institution:
University of Houston
Observed institutions:
Sichuan Agricultural University,
University of Houston
OpenAlex ID:
A5106538928
Harnessing Vision Models for Time Series Analysis: A Survey
2025
·
Jingchao Ni
, Ziming Zhao
, et al.
·
International Joint Conference on Artificial Intelligence
·
45
PDF
Deep Learning-Assisted Rapid Assessment of Food Freshness Using an Anti-interfering Triple-Emission Ratiometric Fluorescent Sensor
2024
·
Chun Wu
, Hongrong Chang
, et al.
·
ACS Sustainable Chemistry & Engineering
·
29
Portable, intelligent MIECL sensing platform for ciprofloxacin detection using a fast convolutional neural networks-assisted Tb@Lu2O3 nanoemitter
2024
·
Zhiwei Lu
, Yonghui Gong
, et al.
·
Food Chemistry
·
27
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
2025
·
ChengAo Shen
, Zhengzhang Chen
, et al.
·
Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
·
19
PDF
Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
2025
·
ChengAo Shen
, Wenchao Yu
, et al.
·
neural information processing systems
·
9
PDF
From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?
2025
·
Zhao, Ziming
, Shen, ChengAo
, et al.
·
arXiv (Cornell University)
·
8
PDF
TSFLab: A Self-Improving Agent-Agnostic Workbench for Time Series Forecasting Research
2026
·
Shen, ChengAo
, Zhao, Yanjun
, et al.
·
arXiv (Cornell University)
PDF
MetaCaster: Meta-Harness-Optimized Agent for End-to-End Few-Shot Learning of Lightweight Time Series Forecasters
2026
·
ChengAo Shen
, Wenchao Yu
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
Harnessing Vision Models for Time Series Analysis: A Survey
2024
·
Jingchao Ni
, Ziming Zhao
, et al.
·
International Joint Conference on Artificial Intelligence
Show more works
View as search
Works count:
10
Citation count:
139
H-index:
6
I10-index:
4
Year
Topic
Type