Time Series

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Period ending 2026-09-21

21 new papers

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  1. Unlocking Temporal Generalization in Hamiltonian Video Dynamics Models

    Jul 8, 2026Eli Laird, Corey ClarkTemporal DynamicsHigh-Fidelity Video Generation

  2. TimEE: End-to-end Time Series Classification via In-Context Learning

    Jul 8, 2026Jaris Küken, Shi Bin Hoo, Martin Mráz +2Time-Series ClassificationModel Pretraining

  3. FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series

    Jul 8, 2026Donato Cerciello, Leonardo Schiavo, Angel Panizo-LLedot +2Time-Series ClassificationTime Series

  4. Rethinking Multimodal Time-Series Forecasting Evaluation

    Jul 8, 2026Haoxin Liu, Yichen Zhou, Rajat Sen +2Zero-Shot ForecastingTime Series

  5. Enhancing deep learning models for time series classification via knowledge distillation

    Jul 7, 2026Javidan Abdullayev, Maxime Devanne, Jonathan Weber +1Knowledge DistillationTime-Series Classification

  6. tsbootstrap: Distribution-Free Uncertainty Quantification and Conformal Prediction for Time Series

    Jul 7, 2026Sankalp GildaMultiplier BootstrapConfidence Intervals

  7. From Jumps to Signatures: a Generative Method for Temporal Point Processes

    Jul 7, 2026Niels Cariou-Kotlarek, Vasileios LamposDeterminantal Point ProcessSynthetic Time Series

  8. RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models

    Jul 7, 2026Qian Sun, Yong-Ming Tian, Jia-Wei Huang +2Time Series Foundation ModelsHigh-Dimensional Data

  9. TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting

    Jul 7, 2026Xiachong Lin, Du Yin, Arian Prabowo +6Zero-Shot ForecastingInternet Of Thing

  10. NEST: Tackling Dataset-Level Distribution Shifts via Regime-Oriented Mixture-of-Experts

    Jul 7, 2026Lanhao Li, Bingshu Xie, Lijun Sun +3Distribution ShiftsMixture-of-Experts Models

  11. VEIL: How Visual Encoding Hijacking Induces Bias In Vision Models

    Jul 6, 2026Suranjana Sooraj, Xuyang Chen, Madhumitha Venkatesan +1Visual AnalyticsTime-Series Classification

  12. Advances in Neural Controlled Differential Equations

    Jul 6, 2026Benjamin WalkerNeural Ordinary Differential EquationsNeural Control

  13. When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters

    Jul 6, 2026Nicholas Tan Jerome, Frank SimonTime Series Foundation ModelsFoundation Model

  14. CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining

    Jul 5, 2026Jingyu Song, Yi Liu, Katherine A. SkinnerVision-Radar FusionAutonomous Driving

  15. Exogenous Dropout: A Simple, Strong Baseline for Corruption-Robust Time Series Forecasting with Covariates

    Jul 5, 2026Hao Hu, Xue-shan AiMultivariate ForecastingTime Series

  16. Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series

    Jul 5, 2026Zitao Shuai, Zongzhe Xu, Yuntian Wu +3Synthetic Time SeriesGenerative Models

  17. Modular Foundation Models for Time-Series Perception in Digital Twins

    Jul 3, 2026Quang Hung Pham, Ryad Zemouri, Martin Gagnon +1Time Series Foundation ModelsWireless Foundation Models

  18. Missingness as Signal: Channel-Independent Spectrogram Learning for Clinical Time Series Prediction

    Jul 3, 2026Soyeon Park, Charmgil HongTime-Series ClassificationMultivariate Time Series Forecasting

  19. PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction

    Jul 3, 2026Zhuoqun Li, Boxi Cao, Jiawei Chen +11Long-Horizon ForecastingNext Activity Prediction

  20. Extreme Adaptive Transformer for Time Series Forecasting

    Jul 2, 2026Sanjeev Shrestha, Hui Liu, Yifan ZhangAccurate Flood PredictionTime Series

  21. Self-Gating Attention for Efficient Time Series Forecasting

    Jul 2, 2026Dezheng Wang, Tong Chen, Wei Yuan +3Multivariate ForecastingTime Series

  22. QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

    Jul 2, 2026Shah Nawaz Haider, Steve Austin, Arnab Barua +2Multivariate ForecastingFoundation Model

  23. SUNTA: Hierarchical Video Prediction with Surprise-based Chunking

    Jul 2, 2026Tomoshi Iiyama, Masahiro Suzuki, Yutaka MatsuoFuture Video PredictionLong-Horizon Forecasting

  24. Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence

    Jul 2, 2026Zhenghua Pan, Ahmed Aziz EzzatElectricity Price ForecastingTime Series Foundation Models

  25. Fast and Accurate Anomaly Detection in Time Series

    Jul 2, 2026Emanuele Mele, Massimo Cafaro, Angelo Coluccia +1Time-Series Anomaly DetectionAnomaly Detection

  26. Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics

    Jul 2, 2026Benedikt Kaas, Manuel Treutlein, Hannes Benedikt Gerber +5Electricity Price ForecastingTime Series Foundation Models

  27. Autorelevance function and other feature relevance measures for univariate time series

    Jul 2, 2026Julian Cardenas, Jamie Arjona, Pedro DelicadoLlm-Based Forecasting MethodsTime Series

  28. Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis

    Jul 2, 2026Yisong Fu, Zezhi Shao, Chengqing Yu +4Time Series Foundation ModelsZero-Shot Forecasting

  29. Evolutionary Feature Engineering for Structured Data

    Jul 2, 2026Ege Onur Taga, Yilin Zhuang, M. Emrullah Ildiz +4Feature EngineeringEvolution

  30. TiRex-2: Generalizing TiRex to Multivariate Data and Streaming

    Jul 1, 2026Patrick Podest, Marco Pichler, Elias Bürger +7Time Series Foundation ModelsMultivariate Forecasting

  31. AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation

    Jul 1, 2026Qingda Hu, Ziheng Qiu, Jieru Zhao +2Visuomotor PolicyMotion Generation

  32. LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning

    Jul 1, 2026Alexander Chemeris, Ming Jin, Randall BalestrieroLatent Bridge MatchingTime-Series Classification

  33. Aionoscope: Debugging Latent-State Accessibility in Time-Series Representations

    Jul 1, 2026Alexander Chemeris, Ming Jin, Randall BalestrieroLatent StatesTime Series

  34. Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

    Jul 1, 2026Seung Hun Han, Hyeongwon Kang, Jinwoo Park +1Time-Series Anomaly DetectionReconstruction-Based Anomaly Detection

  35. Neural Network-Based Estimation of Time-Dependent Parameters in AR(p) Processes

    Jul 1, 2026Agnieszka Kopeć, Paweł Przybyłowicz, Martyna WiącekMultivariate ForecastingPredictive Uncertainty

  36. Timesynth: A Temporal Fidelity Framework for Health Signal Digital Twins

    Jul 1, 2026Md Rakibul Haque, Shireen Elhabian, Warren Woodrich PettinePhysiological DataSynthetic Time Series

  37. StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting

    Jun 30, 2026Haroon Gharwi, Yue Dai, Kai ShuLlm-Based Forecasting MethodsRecurrent State

  38. EVOTS: Evolutionary Transformer Search for Time Series Forecasting

    Jun 30, 2026AbdElRahman ElSaid, Damir PulatovMultivariate Time Series ForecastingEvolutionary Search

  39. Sequential RC-TGAN: Generating Relational Time Series with Spectral Envelope Loss

    Jun 30, 2026Mohamed Gueye, Yazid Attabi, Manuel Morales +1Synthetic Time SeriesTime Series

  40. A time-series classification framework for individual-level absenteeism prediction under severe class imbalance

    Jun 30, 2026Kwong Ho Li, Matthew Roughan, Wathsala KarunarathneTime-Series ClassificationBidirectional Long Short-Term Memory

  41. CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

    Jun 30, 2026Jack Bell, Giacomo Carfi, Gerlando Gramaglia +3CloudZero-Shot Forecasting

  42. A Three-Phase Foundation Model for Tax-Aware Personalized Portfolio Management

    Jun 30, 2026Ramin PishehvarPortfolio OptimizationDeep Reinforcement Learning

  43. Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

    Jun 29, 2026Christopher W. Karvetski, Sheldon S. Huang, Simas Kučinskas +4Prediction MarketsLoad Forecasting

  44. ENC-ODE: Event-level Neurodegenerative Modeling in Continuous Time with Neural ODEs

    Jun 29, 2026Yujee Song, Seunghun Baek, Guorong Wu +1Neural Ordinary Differential EquationsAlzheimer

  45. Temporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model

    Jun 29, 2026Ayşe Betül Yüce, Chris Joey Leffler, Sarun Varghese +2Electroencephalography Foundation ModelsTime Series Foundation Models

  46. Diversity is the Strength of the AI Crowd

    Jun 29, 2026Matthew Aitchison, Scott Jeen, Toby Shevlane +1Load ForecastingDiversity

  47. A Path-Space Formulation of Prediction in World Models: From a Single Action to Prediction, Planning, and Irreversibility

    Jun 27, 2026Gunn KimWorld ModelsLatent Dynamics

  48. MACROCAST: A Vintage-Consistent Time Series Foundation Model for Real-Time Macroeconomic Forecasting

    Jun 27, 2026Andrea Carriero, Davide Pettenuzzo, Shubhranshu ShekharTime Series Foundation ModelsSynthetic Time Series

  49. Improving Patient Subtyping on Longitudinal Data using Representations from Mamba-based Architecture

    Jun 26, 2026Md Mozaharul Mottalib, Rahmatollah BeheshtiLongitudinal DataTime-Series Classification

  50. Improving Coherence in Hierarchical Time Series Forecasting using Structured Temporal Fusion

    Jun 26, 2026Ruchi PakhleMultivariate ForecastingTime Series

  51. GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets

    Jun 26, 2026Janak M. Patel, Anirudh Deodhar, Dagnachew BirruDemand ForecastingLong-Horizon Forecasting

  52. Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA

    Jun 26, 2026Yicheng RuiPhase-Folded Light CurvesTime-Series Classification

  53. Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting

    Jun 26, 2026Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +3Accurate Traffic ForecastingLlm-Based Forecasting Methods

  54. Quantum Dynamic Time Warping for Multivariate Time Series Classification

    Jun 26, 2026Diego Alvarez-Estevez, Alejandro Mayorga-Redondo, Eduardo Mosqueira-ReyHybrid Quantum Neural NetworksQuantum Kernels

  55. Understanding Rollout Error in Graph World Models

    Jun 26, 2026Xinyuan Song, Zekun CaiLong RolloutsWorld Models

  56. The Simulacrum: Decision-Theoretic Pretraining for Near-Optimal Time-Series Forecasting and Inference

    Jun 26, 2026Pablo Montero-Manso, Marcel ScharthMultivariate ForecastingFinite-Sample

  57. Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings

    Jun 26, 2026Taeyeong Choi, Mohammed KamruzzamanTime Series Foundation ModelsOlfactory Perception

  58. Global Explanations for Multivariate Time Series Forecasting Models via KK-Order Markov Approximations

    Jun 25, 2026Amadeo TunyiMultivariate ForecastingMultivariate Time Series Forecasting

  59. Quantum Generative Diffusion Model for Real-World Time Series

    Jun 25, 2026Jack Waller, Filippo Caruso, Dimitrios Makris +2Quantum ComputingSynthetic Data

  60. Unified Zero-Shot Time Series Forecasting: A Darts Foundation

    Jun 25, 2026Zhihao Dai, Dennis Bader, Alain GysiZero-Shot ForecastingLoad Forecasting