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

424 papers, page 5 of 9

201. ICML 2024ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection
202. ICML 2024Explain Temporal Black-Box Models via Functional Decomposition
203. ICML 2024Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems
204. ICML 2024Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
205. ICML 2024Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
206. ICML 2024Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
207. ICML 2024Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees
208. ICML 2024Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
209. ICML 2024Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting
210. ICML 2024Hierarchical Novelty Detection via Fine-Grained Evidence Allocation
211. ICML 2024Incremental Topological Ordering and Cycle Detection with Predictions
212. ICML 2024Infinite-Horizon Distributionally Robust Regret-Optimal Control
213. ICML 2024InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization
214. ICML 2024Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
215. ICML 2024Jacobian Regularizer-based Neural Granger Causality
216. ICML 2024Layerwise Change of Knowledge in Neural Networks
217. ICML 2024Learning Causal Relations from Subsampled Time Series with Two Time-Slices
218. ICML 2024Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
219. ICML 2024Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
220. ICML 2024Learning with Adaptive Resource Allocation
221. ICML 2024Log Neural Controlled Differential Equations: The Lie Brackets Make A Difference
222. ICML 2024Long Range Propagation on Continuous-Time Dynamic Graphs
223. ICML 2024Loss Shaping Constraints for Long-Term Time Series Forecasting
224. ICML 2024Matroid Semi-Bandits in Sublinear Time
225. ICML 2024Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
226. ICML 2024MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
227. ICML 2024MOMENT: A Family of Open Time-series Foundation Models
228. ICML 2024Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
229. ICML 2024Near-Linear Time Approximation Algorithms for k-means with Outliers
230. ICML 2024Network Tight Community Detection
231. ICML 2024Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks
232. ICML 2024Non-parametric Online Change Point Detection on Riemannian Manifolds
233. ICML 2024On the Identifiability of Switching Dynamical Systems
234. ICML 2024Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
235. ICML 2024Optimal Batched Linear Bandits
236. ICML 2024PAC-Bayesian Error Bound, via Rényi Divergence, for a Class of Linear Time-Invariant State-Space Models
237. ICML 2024Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
238. ICML 2024Position: What Can Large Language Models Tell Us about Time Series Analysis
239. ICML 2024Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes
240. ICML 2024Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model
241. ICML 2024Projection-Free Online Convex Optimization with Time-Varying Constraints
242. ICML 2024ReconBoost: Boosting Can Achieve Modality Reconcilement
243. ICML 2024Replicable Learning of Large-Margin Halfspaces
244. ICML 2024Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
245. ICML 2024Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
246. ICML 2024Run-Time Task Composition with Safety Semantics
247. ICML 2024SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
248. ICML 2024Sampling in Unit Time with Kernel Fisher-Rao Flow
249. ICML 2024SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
250. ICML 2024SIN: Selective and Interpretable Normalization for Long-Term 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.