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

875 papers, page 12 of 18

551. ICML 2026TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting
552. ICML 2026TimeLAVA: Learning-Agnostic Valuation for Time Series Data
553. ICML 2026TimeMRA: LLM-Empowered Time Series Forecasting via Multi-Scale Retrieval-Augmented Representations
554. ICML 2026TimeOmni-VL: Unified Models for Time Series Understanding and Generation
555. ICML 2026TimeSAE: Causal Sparse Decoding for Faithful Explanations of Black-Box Time Series Models
556. ICML 2026TimeSeed: Effective Time Series Forecasting with Sparse Endogenous Variables
557. ICML 2026TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
558. ICML 2026TopoDistill: Distilling Global System Topology for Causal Discovery in Multivariate Time Series
559. ICML 2026Towards a Unified Generative Model for Scarce Time Series with Domain Experts
560. ICML 2026Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
561. ICML 2026Towards One-for-All Anomaly Detection for Tabular Data
562. ICML 2026Tri-Scale Neural ODEs for Continuous Multi-Omics Disease Modeling
563. ICML 2026TSFAdv: Frequency-Guided Black-Box Adversarial Attacks on Time Series Forecasting
564. ICML 2026TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
565. ICML 2026TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models
566. ICML 2026Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
567. ICML 2026Unified Time Series Explanations via Amortized Optimization and Instance-level Multi-Expert Knowledge Distillation
568. ICML 2026Universal Redundancies in Time Series Foundation Models
569. ICML 2026WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
570. ICML 2026What if Tomorrow is the World Cup Final? Counterfactual Time Series Forecasting with Textual Conditions
571. ICML 2026What If We Allocate Test-Time Compute Adaptively?
572. ICML 2026What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies
573. ICML 2026WildCat: Near-Linear Attention in Theory and Practice
574. ICML 2026Winformer: Transcending Pairwise Similarity for Time-series Generation
575. ICML 2026Words Towards Explainability: Caption Label-Free Learning via Dual Loop Agentic Time Series Captioning
576. ICML 2026ZeroDiff: Zero-Shot Time Series Reconstruction via Informed-Prior Diffusion
577. ICML 2026Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
578. NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
579. NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
580. NeurIPS 2026A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems
581. NeurIPS 2026A Scalable Multi-Task Model for Virtual Sensors
582. NeurIPS 2026A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature
583. NeurIPS 2026ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space
584. NeurIPS 2026Accelerating Safe Reinforcement Learning with Massive Parallelism
585. NeurIPS 2026ADA: Resolving Attribution Ambiguity in End-to-End Power System Dispatch via Two-Time-Scale Stochastic Approximation
586. NeurIPS 2026Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification
587. NeurIPS 2026AET-Bench: Pixel-Accurate Atomic Tomography Is Not Atom-Accurate
588. NeurIPS 2026AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting
589. NeurIPS 2026Amortized Linear-time Exact Shapley Value for Product-Kernel Methods
590. NeurIPS 2026Anytime-Valid PAC-Bayes Certificates for Adaptive Test-Time Scaling
591. NeurIPS 2026Archimedean Copula Inference via Taylor-Mode AD
592. NeurIPS 2026At FullTilt: Real-Time Open-Set 3D Macromolecule Detection Directly from Tilted 2D Projections
593. NeurIPS 2026AtmoZero: Self-Play Post-Training for Caption-Free Weather Time-Series Captioning
594. NeurIPS 2026Auditing Conformal Prediction for Language Models Under Inference-Time Model Shift
595. NeurIPS 2026Bayesian Preference Learning for Test-Time Steerable Reward Models
596. NeurIPS 2026Bayesian Test-Time Inference of Task-Aligned Similarity from Weak Interactive Feedback
597. NeurIPS 2026Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs
598. NeurIPS 2026Benchmarking Sensor-Fault Robustness in Forecasting
599. NeurIPS 2026Best-of-$N$ Guidance for Test-time Diffusion Alignment
600. NeurIPS 2026Beyond Linear Decoders: Dynamic Expert-Coupled Optimal Decoding for Time Series Forecasting

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.