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 32 of 44

1551. ICLR 2024Explaining Time Series via Contrastive and Locally Sparse Perturbations
1552. ICLR 2024Exploring Diffusion Time-steps for Unsupervised Representation Learning
1553. ICLR 2024Feature-aligned N-BEATS with Sinkhorn divergence
1554. ICLR 2024Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
1555. ICLR 2024FITS: Modeling Time Series with $10k$ Parameters
1556. ICLR 2024FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction
1557. ICLR 2024GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings
1558. ICLR 2024Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
1559. ICLR 2024Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
1560. ICLR 2024Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations
1561. ICLR 2024HyperAttention: Long-context Attention in Near-Linear Time
1562. ICLR 2024IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs
1563. ICLR 2024Incentive-Aware Federated Learning with Training-Time Model Rewards
1564. ICLR 2024Inherently Interpretable Time Series Classification via Multiple Instance Learning
1565. ICLR 2024Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
1566. ICLR 2024iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
1567. ICLR 2024Language Models Represent Space and Time
1568. ICLR 2024Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
1569. ICLR 2024Learning invariant representations of time-homogeneous stochastic dynamical systems
1570. ICLR 2024Learning to Embed Time Series Patches Independently
1571. ICLR 2024Let's do the time-warp-attend: Learning topological invariants of dynamical systems
1572. ICLR 2024Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data
1573. ICLR 2024Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
1574. ICLR 2024LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition
1575. ICLR 2024MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
1576. ICLR 2024MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
1577. ICLR 2024ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis
1578. ICLR 2024MOTOR: A Time-to-Event Foundation Model For Structured Medical Records
1579. ICLR 2024Multi-Resolution Diffusion Models for Time Series Forecasting
1580. ICLR 2024NECO: NEural Collapse Based Out-of-distribution detection
1581. ICLR 2024On Diffusion Modeling for Anomaly Detection
1582. ICLR 2024On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
1583. ICLR 2024Online GNN Evaluation Under Test-time Graph Distribution Shifts
1584. ICLR 2024Parametric Augmentation for Time Series Contrastive Learning
1585. ICLR 2024Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
1586. ICLR 2024Periodicity Decoupling Framework for Long-term Series Forecasting
1587. ICLR 2024Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
1588. ICLR 2024PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
1589. ICLR 2024REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
1590. ICLR 2024Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
1591. ICLR 2024Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
1592. ICLR 2024RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
1593. ICLR 2024Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
1594. ICLR 2024Self-Supervised Contrastive Learning for Long-term Forecasting
1595. ICLR 2024SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
1596. ICLR 2024SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
1597. ICLR 2024Soft Contrastive Learning for Time Series
1598. ICLR 2024Stabilizing Backpropagation Through Time to Learn Complex Physics
1599. ICLR 2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
1600. ICLR 2024STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction

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.