Papers
4,184 papers found
A Theoretical Analysis of Detecting Large Model-Generated Time Series
Junji Hou, Junzhou Zhao, Shuo Zhang et al.
HMformer: Unleashing Transformer’s Potential for Time Series Forecasting via Hierarchical Multi-Scale Modeling
Renjun Huang, Han Xiao, Bingqing Li et al.
M3Time: LLM-Enhanced Multi-Modal, Multi-Scale, and Multi-Frequency Multivariate Time Series Forecasting
Shuning Jia, Baijun Song, Canming Ye et al.
Scaling-up Perceptual Video Quality Assessment
Ziheng Jia, Zicheng Zhang, Xiaorong Zhu et al.
Time Series Forecasting via Direct Per-Step Probability Distribution Modeling
Linghao Kong, Xiaopeng Hong
DeepBooTS: Dual-Stream Residual Boosting for Drift-Resilient Time-Series Forecasting
Daojun Liang, Jing Chen, Xiao Wang et al.
SVGL: Scale-Variable Graph Learning in Model Space for Multivariate Time Series Classification
Shikang Liu, Ziyu Tang, Xiren Zhou et al.
Rethinking Irregular Time Series Forecasting: A Simple Yet Effective Baseline
Xvyuan Liu, Xiangfei Qiu, Xingjian Wu et al.
Sparse-Scale Transformer with Bidirectional Awareness for Time Series Forecasting
Ying Liu, Bo Liu, Sheng Huang et al.
Scaling Law for Large Wireless Models
Ziheng Liu, Jiayi Zhang, Haoyu Wang et al.
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
Sisuo Lyu, Siru Zhong, Weilin Ruan et al.
OmniScale: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo
Qianli Ma, Yaowei Zheng, Zhelun Shi et al.
ReCast: Reliability-aware Codebook-assisted Lightweight Time Series Forecasting
Xiang Ma, Taihua Chen, Pengcheng Wang et al.
Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework
Diego Ortego, Marlon Rodríguez, Mario Almagro et al.
On Stealing Graph Neural Network Models
Marcin Podhajski, Jan Dubiński, Franziska Boenisch et al.
HN-MVTS: HyperNetwork-based Multivariate Time Series Forecasting
Andrey Savchenko, Oleg Kachan
Neural-Augmented Kelvinlet for Real-Time Soft Tissue Deformation Modeling
Ashkan Shahbazi, Kyvia Pereira, Jon S. Heiselman et al.
Finding Time Series Anomalies Using Granular-Ball Vector Data Description
Lifeng Shen, Liang Peng, Ruiwen Liu et al.
Sonnet: Spectral Operator Neural Network for Multivariable Time Series Forecasting
Yuxuan Shu, Vasileios Lampos
WaveFormer: Frequency-Time Decoupled Vision Modeling with Wave Equation
Zishan Shu, Juntong Wu, Wei Yan et al.
MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
Dimitrios Sinodinos, Jack Yi Wei, Narges Armanfard
Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
Dahao Tang, Nan Yang, Yanli Li et al.
Robust SDE Parameter Estimation Under Missing Time Information Setting
Van Long Tran, Truyen Tran, Phuoc Nguyen
Time-Frequency Augmented Multi-level Contrastive Clustering for Time Series
Congyu Wang, Mingjing Du, Xiang Jiang
Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting
Jieting Wang, Huimei Shi, Feijiang Li et al.