Imagen de Portada

Capturing Momentum: Tennis Match Analysis Using Machine Learning and Time Series Theory

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lei, Jingdi, Kang, Tianqi, Cao, Yuluan, Ren, Shiwei
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

HydraNet: Momentum-Driven State Space Duality for Multi-Granularity Tennis Tournaments Analysis
por: Li, Ruijie, et al.
Publicado: (2025)

Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
por: Gao, Haozhi, et al.
Publicado: (2024)

Exact Flow Linear Attention: Exact Solution from Continuous-Time Dynamics
por: Lei, Jingdi, et al.
Publicado: (2025)

Predicting Tennis Serve directions with Machine Learning
por: Zhu, Ying, et al.
Publicado: (2026)

Enhancing Predictive Accuracy in Tennis: Integrating Fuzzy Logic and CV-GRNN for Dynamic Match Outcome and Player Momentum Analysis
por: Li, Kechen, et al.
Publicado: (2025)

Classification of Tennis Actions Using Deep Learning
por: Hovad, Emil, et al.
Publicado: (2024)

A Theory of Machine Learning
por: Kim, Jinsook, et al.
Publicado: (2024)

The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification
por: Middlehurst, Matthew, et al.
Publicado: (2026)

Capture Timing-Attention of Events in Clinical Time Series
por: Li, Jia, et al.
Publicado: (2026)

Differential Machine Learning for Time Series Prediction
por: Yadav, Akash, et al.
Publicado: (2025)

DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting
por: Shu, Yuxuan, et al.
Publicado: (2024)

Momentum LMS Theory beyond Stationarity: Stability, Tracking, and Regret
por: Jin, Yifei, et al.
Publicado: (2026)

Momentum Multi-Marginal Schrödinger Bridge Matching
por: Theodoropoulos, Panagiotis, et al.
Publicado: (2025)

Short-Horizon Predictive Maintenance of Industrial Pumps Using Time-Series Features and Machine Learning
por: Alghtus, Khaled M. A., et al.
Publicado: (2025)

Time Series Analysis in Compressor-Based Machines: A Survey
por: Forbicini, Francesca, et al.
Publicado: (2024)

Rank Supervised Contrastive Learning for Time Series Classification
por: Ren, Qianying, et al.
Publicado: (2024)

Trajectory Generator Matching for Time Series
por: Jahn, T., et al.
Publicado: (2025)

Modeling Tennis In-Match Momentum Using Probability Method
por: Graves, Jackson, et al.
Publicado: (2025)

Capturing Temporal Components for Time Series Classification
por: Vavilthota, Venkata Ragavendra, et al.
Publicado: (2024)

TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis
por: Liu, Jiexi, et al.
Publicado: (2024)

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
por: Cai, Yifu, et al.
Publicado: (2025)

Warping and Matching Subsequences Between Time Series
por: Lin, Simiao, et al.
Publicado: (2025)

mtslearn: Machine Learning in Python for Medical Time Series
por: Jiang, Zhongheng, et al.
Publicado: (2026)

AI for Equitable Tennis Training: Leveraging AI for Equitable and Accurate Classification of Tennis Skill Levels and Training Phases
por: Gao, Gyanna, et al.
Publicado: (2024)

STRGCN: Capturing Asynchronous Spatio-Temporal Dependencies for Irregular Multivariate Time Series Forecasting
por: Wang, Yulong, et al.
Publicado: (2025)

Heavy-Ball Momentum Method in Continuous Time and Discretization Error Analysis
por: Lyu, Bochen, et al.
Publicado: (2025)

Strategy and Skill Learning for Physics-based Table Tennis Animation
por: Wang, Jiashun, et al.
Publicado: (2024)

TS-MLLM: A Multi-Modal Large Language Model-based Framework for Industrial Time-Series Big Data Analysis
por: Wang, Haiteng, et al.
Publicado: (2026)

Adaptive Modeling of Satellite-Derived Nighttime Lights Time-Series for Tracking Urban Change Processes Using Machine Learning
por: Chakraborty, Srija, et al.
Publicado: (2023)

Momentum Capture and Prediction System Based on Wimbledon Open2023 Tournament Data
por: Liu, Chang, et al.
Publicado: (2024)

Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
por: Zhang, Ziyi, et al.
Publicado: (2024)

From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap
por: Kou, Tianqi
Publicado: (2024)

Dataset Condensation for Time Series Classification via Dual Domain Matching
por: Liu, Zhanyu, et al.
Publicado: (2024)

Automated Contrastive Learning Strategy Search for Time Series
por: Jing, Baoyu, et al.
Publicado: (2024)

TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
por: Wang, Shiyu, et al.
Publicado: (2024)

IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems
por: Oppel, Heiko, et al.
Publicado: (2024)

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis
por: Talukder, Sabera, et al.
Publicado: (2024)

Deep Learning For Time Series Analysis With Application On Human Motion
por: Ismail-Fawaz, Ali
Publicado: (2025)

Robotic Table Tennis: A Case Study into a High Speed Learning System
por: D'Ambrosio, David B., et al.
Publicado: (2023)

NeuroPathNet: Dynamic Path Trajectory Learning for Brain Functional Connectivity Analysis
por: Guo, Tianqi, et al.
Publicado: (2025)