Key papers

• Kolmogorov-Arnold Networks (KANs) for Time Series Analysis (2024)
  Cristian J. Vaca-Rubio et al.
  10.12
• Recurrent Auto-Encoder Model for Large-Scale Industrial Sensor Signal Analysis (2018)
  Timothy Wong et al.
  6.24
• Trajectory Data Mining and Trip Travel Time Prediction on Specific Roads (2024)
  Muhammad Awais Amin et al.
  4.85
• Laplacian Convolutional Representation for Traffic Time Series Imputation (2022)
  Xinyu Chen and Zhanhong Cheng and HanQin Cai and Nicolas Saunier and Lijun Sun
  4.79
• Multi-layer MIMO Relay as Deep Physical Neural Networks: Power Amplifiers as Activation Functions (2026)
  Meng Hua et al.
  4.39
• Multiple cyclicity and Wavelet Decomposition with Channel Correlation for Long-term Time Series Forecasting (2026)
  Bin Wang et al.
  4.33
• Real-time Bus Travel Time Prediction and Reliability Quantification: A Hybrid Markov Model (2025)
  Yuran Sun et al.
  4.30
• Bounds in Wasserstein Distance for Locally Stationary Functional Time Series (2025)
  Jan Nino G. Tinio et al.
  3.70
• FreIE: Low-Frequency Spectral Bias in Neural Networks for Time-Series Tasks (2025)
  Jialong Sun et al.
  3.10
• Improving Internet Traffic Matrix Prediction via Time Series Clustering (2025)
  Martha Cash et al.
  3.04
• A time warping model for seasonal data with application to age estimation from narwhal tusks (2024)
  Lars N{\o}rtoft Reiter et al.
  2.49
• Linguistic Approach to Time Series Forecasting (2022)
  Dmytro Lande et al.
  2.26
• Water Level Forecasting in the Gamcheon River, Korea, Using TimeGPT (2026)
  Jon-Lark Kim et al.
  1.94
• TimeGPT for Mechanical System Degradation Assessment: A Large Time Series Model Approach (2026)
  Junyu Qi et al.
  1.94
• PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting (2026)
  Yingbo Zhou et al.
  1.89
• Time-Series Classification with Multivariate Statistical Dependence Features (2026)
  Yao Sun et al.
  1.83
• FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting (2026)
  Boya Zhang et al.
  1.78
• TimeAPN: Adaptive Amplitude-Phase Non-Stationarity Normalization for Time Series Forecasting (2026)
  Yue Hu et al.
  1.78
• TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series (2026)
  Xihao Piao et al.
  1.72
• Fast Mining and Dynamic Time-to-Event Prediction over Multi-sensor Data Streams (2026)
  Kota Nakamura et al.
  1.67
• AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs (2026)
  Ting Dang et al.
  1.67
• FreDN: Spectral Disentanglement for Time Series Forecasting via Learnable Frequency Decomposition (2025)
  Zhongde An et al.
  1.56
• WaveTuner: Comprehensive Wavelet Subband Tuning for Time Series Forecasting (2025)
  Yubo Wang and Hui He and Chaoxi Niu and Zhendong Niu
  1.56
• ATLO-ML: Adaptive Time-Length Optimizer for Machine Learning -- Insights from Air Quality Forecasting (2025)
  I-Hsi Kao et al.
  1.50
• A Deep Learning Approach for Spatio-Temporal Forecasting of InSAR Ground Deformation in Eastern Ireland (2025)
  Wendong Yao et al.
  1.44
• Stationarity Exploration for Multivariate Time Series Forecasting (2025)
  Hao Liu and Chun Yang and Zhang xiaoxing and Rui Ma and Xiaobin Zhu
  1.39
• Spectrum Prediction in the Fractional Fourier Domain with Adaptive Filtering (2025)
  Yanghao Qin et al.
  1.39
• Optimizing Basis Function Selection in Constructive Wavelet Neural Networks and Its Applications (2025)
  Dunsheng Huang et al.
  1.33
• Sugar-Beet Stress Detection using Satellite Image Time Series (2025)
  Bhumika Laxman Sadbhave et al.
  1.33
• PAF-Net: Phase-Aligned Frequency Decoupling Network for Multi-Process Manufacturing Quality Prediction (2025)
  Yang Luo and Haoyang Luan and Haoyun Pan and Yongquan Jia and Xiaofeng Gao and Guihai Chen
  1.33
• TFKAN: Time-Frequency KAN for Long-Term Time Series Forecasting (2025)
  Xiaoyan Kui and Canwei Liu and Qinsong Li and Zhipeng Hu and Yangyang Shi and Weixin Si and Beiji Zou
  1.28
• LSCD: Lomb-Scargle Conditioned Diffusion for Time series Imputation (2025)
  Elizabeth Fons et al.
  1.28
• Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting (2025)
  Ziyu Zhou et al.
  1.22
• TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning (2025)
  Ron Shapira Weber et al.
  1.22
• Block Toeplitz Sparse Precision Matrix Estimation for Large-Scale Interval-Valued Time Series Forecasting (2025)
  Wan Tian et al.
  1.17
• Efficient Time Series Forecasting via Hyper-Complex Models and Frequency Aggregation (2025)
  Eyal Yakir et al.
  1.06
• Investigating the performance of the Phase II Hotelling T2 chart when monitoring multivariate time series observations (2025)
  Adel Ahmadi Nadi et al.
  1.00
• Forecasting Automotive Supply Chain Shortfalls with Heterogeneous Time Series (2024)
  Bach Viet Do et al.
  0.72
• A novel Reservoir Architecture for Periodic Time Series Prediction (2024)
  Zhongju Yuan et al.
  0.61
• Phase-driven Domain Generalizable Learning for Nonstationary Time Series (2024)
  Payal Mohapatra et al.
  0.44
• SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation (2023)
  Hyun Ryu et al.
  0.33
• A Heavy-Load-Enhanced and Changeable-Periodicity-Perceived Workload Prediction Network (2023)
  Feiyi Chen et al.
  0.11
• Dense Bag-of-Temporal-SIFT-Words for Time Series Classification (2016)
  Adeline Bailly (LETG - Costel et al.
  —
• Time and Activity Sequence Prediction of Business Process Instances (2016)
  Mirko Polato et al.
  —
• Comparing Time and Frequency Domain for Audio Event Recognition Using Deep Learning (2016)
  Lars Hertel et al.
  —
• metricDTW: local distance metric learning in Dynamic Time Warping (2016)
  Jiaping Zhao et al.
  —
• Out-of-Sample Extension for Dimensionality Reduction of Noisy Time Series (2016)
  Hamid Dadkhahi and Marco F. Duarte and Benjamin Marlin
  —
• End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks (2016)
  Timothy J. O'Shea et al.
  —
• Adaptive Forecasting of Non-Stationary Nonlinear Time Series Based on the Evolving Weighted Neuro-Neo-Fuzzy-ANARX-Model (2016)
  Zhengbing Hu et al.
  —
• Earliness-Aware Deep Convolutional Networks for Early Time Series Classification (2016)
  Wenlin Wang et al.
  —
• Temporal Feature Selection on Networked Time Series (2016)
  Haishuai Wang et al.
  —
• See the Near Future: A Short-Term Predictive Methodology to Traffic Load in ITS (2017)
  Xun Zhou et al.
  —
• Soft-DTW: a Differentiable Loss Function for Time-Series (2017)
  Marco Cuturi and Mathieu Blondel
  —
• A time series distance measure for efficient clustering of input output signals by their underlying dynamics (2017)
  Oliver Lauwers et al.
  —
• Hot or not? Forecasting cellular network hot spots using sector performance indicators (2017)
  Joan Serr\`a et al.
  —
• Machine learning modeling for time series problem: Predicting flight ticket prices (2017)
  Jun Lu
  —
• Feature-based time-series analysis (2017)
  Ben D. Fulcher
  —
• Role of Deep LSTM Neural Networks And WiFi Networks in Support of Occupancy Prediction in Smart Buildings (2017)
  Basheer Qolomany et al.
  —
• Short-Term Prediction of Signal Cycle in Actuated-Controlled Corridor Using Sparse Time Series Models (2017)
  Bahman Moghimi et al.
  —
• Multi-task learning of time series and its application to the travel demand (2017)
  Boris Chidlovskii
  —