Time Series papers, 2023–2026

Key findings

• Time Series went from 272 papers in 2023 to 876 in 2026, roughly 3.2x in three years.
• NeurIPS publishes the most Time Series work: 757 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 6 in 2023 to 85 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #1 by 2026 paper count; the fastest grower in the group, Molecular Modeling, is up 2.7x versus 3.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026Activation Matters Test-time Activated Negative Labels for OOD Detection with
• NeurIPS 2025Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
• ICML 2025$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
• ICLR 2025A deep inverse-mapping model for a flapping robotic wing
• CVPR 2025Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization
• NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
• ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
• ICLR 2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
• CVPR 2024Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
• NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
• ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
• ICLR 2023A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
• CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
• NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
• ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
• ICLR 2026A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
• CVPR 2026Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis

All Time Series papers

2,156 papers, page 35 of 44

1701. ICML 2024Projection-Free Online Convex Optimization with Time-Varying Constraints
1702. ICML 2024ReconBoost: Boosting Can Achieve Modality Reconcilement
1703. ICML 2024Replicable Learning of Large-Margin Halfspaces
1704. ICML 2024Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
1705. ICML 2024Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
1706. ICML 2024Run-Time Task Composition with Safety Semantics
1707. ICML 2024SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
1708. ICML 2024Sampling in Unit Time with Kernel Fisher-Rao Flow
1709. ICML 2024SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
1710. ICML 2024SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting
1711. ICML 2024Sparsest Models Elude Pruning: An Exposé of Pruning’s Current Capabilities
1712. ICML 2024SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters
1713. ICML 2024Stealing part of a production language model
1714. ICML 2024Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction
1715. ICML 2024TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision
1716. ICML 2024Test-Time Degradation Adaptation for Open-Set Image Restoration
1717. ICML 2024Test-Time Model Adaptation with Only Forward Passes
1718. ICML 2024Test-Time Regret Minimization in Meta Reinforcement Learning
1719. ICML 2024The Fundamental Limits of Least-Privilege Learning
1720. ICML 2024Time Series Diffusion in the Frequency Domain
1721. ICML 2024Time Weaver: A Conditional Time Series Generation Model
1722. ICML 2024Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
1723. ICML 2024TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
1724. ICML 2024Timer: Generative Pre-trained Transformers Are Large Time Series Models
1725. ICML 2024TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
1726. ICML 2024TimeX++: Learning Time-Series Explanations with Information Bottleneck
1727. ICML 2024Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
1728. ICML 2024TSLANet: Rethinking Transformers for Time Series Representation Learning
1729. ICML 2024ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback
1730. ICML 2024Unified Training of Universal Time Series Forecasting Transformers
1731. ICML 2024UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
1732. ICML 2024Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection
1733. ICML 2024Variational Schrödinger Diffusion Models
1734. ICML 2024Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment
1735. ICML 2024Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
1736. ICML 2024What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement
1737. ICML 2024When and How Does In-Distribution Label Help Out-of-Distribution Detection?
1738. NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
1739. NeurIPS 2024A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds
1740. NeurIPS 2024Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
1741. NeurIPS 2024Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
1742. NeurIPS 2024Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
1743. NeurIPS 2024Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting
1744. NeurIPS 2024Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
1745. NeurIPS 2024Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
1746. NeurIPS 2024Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting
1747. NeurIPS 2024ANT: Adaptive Noise Schedule for Time Series Diffusion Models
1748. NeurIPS 2024Are Language Models Actually Useful for Time Series Forecasting?
1749. NeurIPS 2024Are Self-Attentions Effective for Time Series Forecasting?
1750. NeurIPS 2024Asynchronous Perception Machine for Efficient Test Time Training

FAQ

How many Time Series papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,157 in total: 272 in 2023, 424 in 2024, 585 in 2025, 876 in 2026.

How many Time Series papers are at NeurIPS 2026?

NeurIPS 2026 has 298 Time Series papers, versus 221 the year before.

How many Time Series papers are at ICLR 2026?

ICLR 2026 has 220 Time Series papers, versus 131 the year before.

How many Time Series papers are at ICML 2026?

ICML 2026 has 264 Time Series papers, versus 159 the year before.

How many Time Series papers are at CVPR 2026?

CVPR 2026 has 94 Time Series papers, versus 74 the year before.

Which conference publishes the most Time Series papers?

NeurIPS, with 757 papers from 2023 to 2026.