Haotian Gao
Scholar

Haotian Gao

Google Scholar ID: J0ku0GcAAAAJ
The University of Tokyo
Spatiotemporal forecastingSelf-supervised learningTime series forecasting
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Citations & Impact
All-time
Citations
133
 
H-index
2
 
i10-index
2
 
Publications
3
 
Co-authors
5
list available
Contact
No contact links provided.
Publications
8 items
SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models
2026
Cited
0
RUQuant: Towards Refining Uniform Quantization for Large Language Models
2026
Cited
0
Towards Effective Orchestration of AI x DB Workloads
2026
Cited
0
PLANET v2.0: A comprehensive Protein-Ligand Affinity Prediction Model Based on Mixture Density Network
2026
Cited
0
How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learning
2025
Cited
0
NeurBench: Benchmarking Learned Database Components with Data and Workload Drift Modeling
2025
Cited
0
COMET:Combined Matrix for Elucidating Targets
2024
Cited
0
NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
arXiv.org · 2024
Cited
0
Resume (English only)
Co-authors
5 total
Renhe Jiang
Renhe Jiang
The University of Tokyo
Co-author 2
Co-author 2
Xuan Song
Xuan Song
Dean and Professor, School of Artificial Intelligence, Jilin University; SUSTech
Jinliang Deng
Jinliang Deng
Postdoctoral Fellow, Hong Kong University of Science and Technology
Hangchen Liu
Hangchen Liu
The University of Tokyo