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

757 papers, page 14 of 16

651. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
652. NeurIPS 2024TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
653. NeurIPS 2024Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
654. NeurIPS 2024Towards Editing Time Series
655. NeurIPS 2024Towards Understanding Evolving Patterns in Sequential Data
656. NeurIPS 2024TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation
657. NeurIPS 2024Trajectory Flow Matching with Applications to Clinical Time Series Modelling
658. NeurIPS 2024Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
659. NeurIPS 2024TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
660. NeurIPS 2024UniMTS: Unified Pre-training for Motion Time Series
661. NeurIPS 2024UniTS: A Unified Multi-Task Time Series Model
662. NeurIPS 2024Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
663. NeurIPS 2024Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series
664. NeurIPS 2024When are dynamical systems learned from time series data statistically accurate?
665. NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
666. NeurIPS 2024YOLOv10: Real-Time End-to-End Object Detection
667. NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
668. NeurIPS 2023Active Observing in Continuous-time Control
669. NeurIPS 2023Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
670. NeurIPS 2023Adaptive Test-Time Personalization for Federated Learning
671. NeurIPS 2023Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
672. NeurIPS 2023ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation
673. NeurIPS 2023Bandit Task Assignment with Unknown Processing Time
674. NeurIPS 2023BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
675. NeurIPS 2023Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability
676. NeurIPS 2023Bifurcations and loss jumps in RNN training
677. NeurIPS 2023BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series
678. NeurIPS 2023BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
679. NeurIPS 2023Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing
680. NeurIPS 2023Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
681. NeurIPS 2023Cal-DETR: Calibrated Detection Transformer
682. NeurIPS 2023Causal Discovery from Subsampled Time Series with Proxy Variables
683. NeurIPS 2023Causal Discovery in Semi-Stationary Time Series
684. NeurIPS 2023Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker
685. NeurIPS 2023Conformal PID Control for Time Series Prediction
686. NeurIPS 2023Conformal Prediction for Time Series with Modern Hopfield Networks
687. NeurIPS 2023Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards
688. NeurIPS 2023ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
689. NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
690. NeurIPS 2023Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series
691. NeurIPS 2023CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement
692. NeurIPS 2023Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
693. NeurIPS 2023Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization
694. NeurIPS 2023Drift doesn't Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection
695. NeurIPS 2023Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
696. NeurIPS 2023Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
697. NeurIPS 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
698. NeurIPS 2023Finite-Time Analysis of Single-Timescale Actor-Critic
699. NeurIPS 2023Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation
700. NeurIPS 2023Finite-Time Logarithmic Bayes Regret Upper Bounds

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.