Time Series Forecasting

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139 papers in the last four weeks, up 101% on the four weeks before. 0.9% of all new papers.

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Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS
May 12, 2026Gaspard Berthelier, Mariia Baranova, Andrei-Tiberiu Pantea +4Multivariate Time Series Forecasting Time Series Forecasting
EDF R&D, Palaiseau · Inria Sophia-Antipolis, Université Côte d’Azur · Université Paris Cit'e
ECTO: Exogenous-Conditioned Temporal Operator for Ultra-Short-Term Wind Power Forecasting
May 12, 2026Cao Yuan, Junjun WangTime Series Forecasting Non-Stationary Time Series Forecasting
Wuhan Polytechnic University, Wuhan, 430048, Hubei, China
From Index to Equity: Pre-Training Transformers for Stock Return Prediction
May 12, 2026Marie Soehl Coolsaet, Roberto Gallardo, Zhen GaoTime Series Forecasting Transfer Learning
Faculty of Engineering, McMaster University · Department* of Economics, Universidad Veracruzana, Mexico
Dual-Temporal LSTM with Hybrid Attention for Airline Passenger Load Factor Forecasting: Integrating Intra-Flight and Inter-Flight Booking Dynamics
May 12, 2026ASM Nazrul Islam, Md. Hasanul Kabir, Md. Liakot Ali +1Time Series Forecasting Long Short-Term Memory Networks
Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh · Islamic University of Technology, Dhaka, Bangladesh
Beyond Similarity: Temporal Operator Attention for Time Series Analysis
May 11, 2026Jevon Twitty, Vinh Pham, Nitiwith Rotchanarak +4Time Series Classification Time Series Forecasting
Georgia Institute of Technology1
Latent Chain-of-Thought Improves Structured-Data Transformers
May 11, 2026Carson Dudley, Samet OymakCoT Reasoning Time Series Forecasting
NoRIN: Backbone-Adaptive Reversible Normalization for Time-Series Forecasting
May 11, 2026Shun Zhang, Yuyang XiaoTime Series Forecasting
Graduate School of China Academy of Engineering Physics, Beijing 100193, China · Institute of Applied Physics and Computational Mathematics, Beijing 100094, China
Benchmarking Sensor-Fault Robustness in Forecasting
May 11, 2026Alexander Windmann, Philipp Wittenberg, Gianluca Manca +3Cyber-Physical Systems Time Series Forecasting
1Helmut Schmidt University · 2Ruhr University Bochum · 3ABB Corporate Research +2
DeepLévy: Learning Heavy-Tailed Uncertainty in Highly Volatile Time Series
May 11, 2026Yang Yang, Du Yin, Hao Xue +1Time Series Forecasting Distribution Matching
University of New South Wales Australia NSW Sydney · The Hong Kong University of Science and Technology (Guangzhou)
Fast Training of Mixture-of-Experts for Time Series Forecasting via Expert Loss Integration
May 11, 2026Btissame El Mahtout, Florian ZielTime Series Forecasting Mixture-of-Experts Models
Chair of Data Science in Energy and Environment, University of Duisburg-Essen, Germany · Chair of Econometrics and Statistics, Technical University of Dortmund, Germany
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
May 11, 2026Sheng Pan, Ming Jin, Bo Du +1Neural Controlled Differential Equations Time Series Forecasting
Griffith University
Game-Theoretic Modeling of Heterogeneous Investor Interactions for Stock Price Forecasting
May 11, 2026Yong Zhang, Xinxiao Wu, Yunde Jia +1Quantitative Finance Time Series Forecasting
School of Computer Science, Beijing Institute of Technology · Faculty of Engineering, Shenzhen MSU-BIT University
Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis
May 11, 2026Aman Singh, Tokunbo Ogunfunmi, Sanjiv DasQuantitative Finance Time Series Forecasting
Department of Electrical and Computer Engineering, Santa Clara University, USA · School of Business, Santa Clara University, USA
Benchmarking Transformer and xLSTM for Time-Series Forecasting of Heat Consumption
May 10, 2026Marja Wahl, Daniel R. Bayer, Sven Rausch +1Energy-Efficient ML Time Series Forecasting
RAUSCH Technology GmbH, Würzburg, Germany · Modeling and Simulation, University of Würzburg, Würzburg, Germany
Spectral Transformer Neural Processes
May 10, 2026Xianhe Chen, Hao Chen, Yingzhen LiTransformer Neural Processes
University of Cambridge · Tencent · Imperial College London
SSDA: Bridging Spectral and Structural Gaps via Dual Adaptation for Vision-Based Time Series Forecasting
May 10, 2026Mingrui Zhang, Hanchen Yang, Wengen Li +4Domain Adaptation Time Series Forecasting
TSNN: A Non-parametric and Interpretable Framework for Traffic Time Series Forecasting
May 9, 2026Bowen Liu, Haijian Lai, Chan-Tong Lam +4Time Series Forecasting Traffic Forecasting
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China
A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting
May 9, 2026Runyao Yu, Julia Lin, Derek W. Bunn +6Electricity Price Forecasting Time Series Forecasting
Delft University of Technology · Austrian Institute of Technology · London Business School +2
Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift
May 9, 2026Bong Gyun Shin, Chan Sik Lee, Hyesun SuhDistribution Shift Robustness Time Series Forecasting
Department of AI Big Data, Daejin University, 1007 Hoguk-ro,2026 Pocheon-si, Gyeonggi-do, 11159, Republic of Korea. · Department of Statistics and Actuarial Science, Soongsil University, 50 Sadang-ro, Dongjak-gu, Seoul, 06978, Republic of Korea. · College of Artificial Intelligence Convergence, Daejin University, 1007 Hoguk-ro, Pocheon-si, Gyeonggi-do, 11159, Republic of Korea.
A Quantum Inspired Variational Kernel and Explainable AI Framework for Cross Region Solar and Wind Energy Forecasting
May 9, 2026Pavan Manjunath, Thomas PruferTime Series Forecasting Quantum-Inspired ML
Independent Research Scholar, Germany
TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification
May 9, 2026Xinyu Chen, HanQin Cai, Lijun Ding +1Time Series Forecasting Heavy-Tailed Noise
University of Central Florida Orlando, FL 32816 · Massachusetts Institute of Technology Cambridge, MA 02139
RareCP: Regime-Aware Retrieval for Efficient Conformal Prediction
May 9, 2026Manuel Heurich, Maximilian Granz, Tim LandgrafWeighted Conformal Prediction Time Series Forecasting
Institute for Computer Science Freie Universität Berlin Arnimallee 7 14195 Berlin
LEAF: A Living Benchmark for Event-Augmented Forecasting
May 9, 2026Mingtian Tan, Mihir Parmar, Palash Goyal +5Financial Forecasting Time Series Forecasting
Google · University of Virginia
Reasoning-Aware Training for Time Series Forecasting
May 9, 2026Md Atik Ahamed, Mihir Parmar, Palash Goyal +4Time Series Reasoning Time Series Forecasting
1Google · University of Kentucky
STEPS: A Temporal Smooth Error Propagation Solver on the Manifolds for Test-Time Adaptation in Time Series Forecasting
May 8, 2026Jiaqi Liu, Yifan Ouyang, Zhifei Song +2Source-Free Domain Adaptation Test-Time Adaptation
School of Artificial Intelligence and Robotics, Xiamen University Malaysia · S.M.A.R.T. NEXUS Centre of Excellence, Xiamen University Malaysia Sepang, Selangor 43900, Malaysia
NPMixer: Hierarchical Neighboring Patch Mixing for Time Series Forecasting
May 8, 2026Jung Min Choi, Vijaya Krishna Yalavarthi, Lars Schmidt-ThiemeMultivariate Time Series Forecasting Time Series Forecasting
1ISMLL, University of Hildesheim, VWFS Data Analytics Research Center (VWFS-DARC), Hildesheim, Germany.
What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies
May 8, 2026Fan Zhang, Shiming Fan, Hua WangMultivariate Time Series Forecasting Feature Interaction Modeling
Shandong Technology and Business University, Yantai, Shandong, China · Ludong University, Yantai, Shandong, China
Exactness Matters for Physical Rule Enforcement
May 8, 2026Bum Jun KimTime Series Forecasting Spatiotemporal Forecasting
The University of Tokyo, Japan
Don't Learn the Shape: Forecasting Periodic Time Series by Rank-1 Decomposition
May 8, 2026Takato HondaLow-Rank Matrix Decomposition Time Series Forecasting
Mellon Inc.
Dual-Scale Temporal Fusion Reveals Structured Predictability in Subseasonal-to-Seasonal Temperature Prediction
May 7, 2026Elnaz Bashir, Jiali Wang, Lin YanTime Series Forecasting Multi-Scale Feature Fusion
Department of Computer Science, Iowa State University, Ames, IA 50011, USA · Environmental Science Division, Argonne National Laboratory, Lemont, IL 60439, USA

May 12, 2026, cs.LGJ/K move · Enter open · S save

Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS

Gaspard Berthelier, Mariia Baranova, Andrei-Tiberiu Pantea, Etienne Le Naour+3

EDF R&D, Palaiseau · Inria Sophia-Antipolis, Université Côte d’Azur · Université Paris Cit'e

Multivariate Time Series Forecasting Time Series Forecasting Time-Series Foundation Models

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Time Series Foundation Models (TSFMs) have recently achieved state-of-the-art performance, often outperforming supervised models in zero-shot settings. Recent TSFM architectures, such as Chronos-2 and TabPFN-TS, aim to integrate covariates. In this paper, we design controlled experiments based on simple target-covariate relationships to assess this integration capability. Our results show that TabPFN-TS captures these relationships more effectively than Chronos-2, especially for short horizons, suggesting that the strong benchmark performance of Chronos-2 does not automatically translate into optimal modeling of simple covariate-target dependencies.