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 7 of 44

301. ICLR 2026TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
302. ICLR 2026Understanding the Implicit Biases of Design Choices for Time Series Foundation Models
303. ICLR 2026UNDERSTANDING TRANSFORMERS FOR TIME SEIRES FORECASTING: A CASE STUDY ON MOIRAI
304. ICLR 2026Understanding Transformers for Time Series: Rank Structure, Flow-of-ranks, and Compressibility
305. ICLR 2026UniCA: Unified Covariate Adaptation for Time Series Foundation Model
306. ICLR 2026Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecasting
307. ICLR 2026Unmasking Backdoors: An Explainable Defense via Gradient-Attention Anomaly Scoring for Pre-trained Language Models
308. ICLR 2026Weight-Space Linear Recurrent Neural Networks
309. ICLR 2026When and Where to Reset Matters for Long-Term Test-Time Adaptation
310. ICLR 2026When Foundation Models are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection
311. ICLR 2026When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
312. ICLR 2026xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
313. ICLR 2026Zero-shot Forecasting by Simulation Alone
314. ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
315. ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
316. ICML 2026A Decision-Theoretic View of Test-Time Training: When, How Far, and Which Directions to Adapt
317. ICML 2026A robust PPG foundation model using multimodal physiological supervision
318. ICML 2026A Spiking Heterogeneous Harmonic Resonate-and-Fire State Space Model for Time Series
319. ICML 2026A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching
320. ICML 2026Accurate Evaluation of Quickest Changepoint Detectors via Non-parametric Survival Analysis
321. ICML 2026AdaMEM: Test-Time Adaptive Memory for Language Agents
322. ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
323. ICML 2026Adversarially Robust Approximate Furthest Neighbor
324. ICML 2026Anti-Aliasing Matters: A Dynamic Network for Time Series Forecasting
325. ICML 2026AsyncSpade: Efficient Test-Time Scaling with Asynchronous Sparse Decoding
326. ICML 2026ATLAS: Learning to Optimally Memorize the Context at Test Time
327. ICML 2026Automatic Unsupervised Ensemble Outlier Model Selection
328. ICML 2026Baguan-TS: dual in-context learning model for time series forecasting with covariates
329. ICML 2026BEDTime: A Unified Benchmark for Automatically Describing Time Series
330. ICML 2026Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
331. ICML 2026Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting
332. ICML 2026Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
333. ICML 2026Beyond Point Predictions: Manifold Expansion and Dual Alignment for Robust Time Series Distillation
334. ICML 2026Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
335. ICML 2026BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series
336. ICML 2026Bootstrapped Exploration with Causal Reasoning: A Training Paradigm for Adaptive Forecasting Agent
337. ICML 2026Branching Diffusion for Point Processes in Time and Space
338. ICML 2026Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time
339. ICML 2026Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting
340. ICML 2026Byte Pair Encoding for Efficient Time Series Forecasting
341. ICML 2026Calibrated Test-Time Guidance for Bayesian Inference
342. ICML 2026Causal Discovery for Irregularly Time Series with Consistency Guarantees
343. ICML 2026Causal discovery for time series with endogenous context variables
344. ICML 2026Causal-aware Anomaly Detection for Tabular Data
345. ICML 2026CausalX: A Unified and Causally-Interpretable Plug-and-Play Model for Multi-modal Spatio-Temporal Forecasting
346. ICML 2026Channel Adapter for Time Series Foundation Models in Zero-Shot Multivariate Forecasting
347. ICML 2026CHESS: Chebyshev Spectral Synthesis for Trajectory Condensation
348. ICML 2026Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series
349. ICML 2026CoGenCast: A Coupled Autoregressive–Flow Generative Framework for Time Series Forecasting
350. ICML 2026COGNOS: Universal Enhancement for Time Series Anomaly Detection via Constrained Gaussian-Noise Optimization and Smoothing

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.