most citedEffectively Modeling Time Series with Simple Discrete State Spaces

15 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

Enabling CMF Estimation in Data-Constrained Scenarios: A Semantic-Encoding Knowledge Mining Model

Yanlin Qi, Jia Li, Michael Zhang

Precise estimation of Crash Modification Factors (CMFs) is central to evaluating the effectiveness of various road safety treatments and prioritizing infrastructure investment acco…

eess.SY2023

Joint Optimization of Traffic Signal Control and Vehicle Routing in Signalized Road Networks using Multi-Agent Deep Reinforcement Learning

Xianyue Peng, Hang Gao, Gengyue Han +2

Urban traffic congestion is a critical predicament that plagues modern road networks. To alleviate this issue and enhance traffic efficiency, traffic signal control and vehicle rou…

cs.AI20231 cited

EVKG: An Interlinked and Interoperable Electric Vehicle Knowledge Graph for Smart Transportation System

Yanlin Qi, Gengchen Mai, Rui Zhu +1

Over the past decade, the electric vehicle industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multiface…

cs.LG202315 cited

Effectively Modeling Time Series with Simple Discrete State Spaces

Michael Zhang, Khaled K. Saab, Michael Poli +3

Time series modeling is a well-established problem, which often requires that methods (1) expressively represent complicated dependencies, (2) forecast long horizons, and (3) effic…

cs.LG20236 cited

Simple Hardware-Efficient Long Convolutions for Sequence Modeling

Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen +5

State space models (SSMs) have high performance on long sequence modeling but require sophisticated initialization techniques and specialized implementations for high quality and r…

cs.LG202212 cited

Contrastive Adapters for Foundation Model Group Robustness

Michael Zhang, Christopher Ré

While large pretrained foundation models (FMs) have shown remarkable zero-shot classification robustness to dataset-level distribution shifts, their robustness to subpopulation or…