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

272 papers, page 5 of 6

201. NeurIPS 2023Conformal Prediction for Time Series with Modern Hopfield Networks
202. NeurIPS 2023Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards
203. NeurIPS 2023ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
204. NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
205. NeurIPS 2023Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series
206. NeurIPS 2023CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement
207. NeurIPS 2023Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
208. NeurIPS 2023Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization
209. NeurIPS 2023Drift doesn't Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection
210. NeurIPS 2023Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency
211. NeurIPS 2023Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
212. NeurIPS 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
213. NeurIPS 2023Finite-Time Analysis of Single-Timescale Actor-Critic
214. NeurIPS 2023Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation
215. NeurIPS 2023Finite-Time Logarithmic Bayes Regret Upper Bounds
216. NeurIPS 2023FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space
217. NeurIPS 2023ForecastPFN: Synthetically-Trained Zero-Shot Forecasting
218. NeurIPS 2023FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
219. NeurIPS 2023Frequency-domain MLPs are More Effective Learners in Time Series Forecasting
220. NeurIPS 2023Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time
221. NeurIPS 2023Geometric Neural Diffusion Processes
222. NeurIPS 2023GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
223. NeurIPS 2023Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians
224. NeurIPS 2023Granger Components Analysis: Unsupervised learning of latent temporal dependencies
225. NeurIPS 2023GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
226. NeurIPS 2023Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
227. NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
228. NeurIPS 2023Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
229. NeurIPS 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
230. NeurIPS 2023Large Language Models Are Zero-Shot Time Series Forecasters
231. NeurIPS 2023Latent SDEs on Homogeneous Spaces
232. NeurIPS 2023Linear Time Algorithms for k-means with Multi-Swap Local Search
233. NeurIPS 2023Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction
234. NeurIPS 2023MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection
235. NeurIPS 2023Most Neural Networks Are Almost Learnable
236. NeurIPS 2023Near-Linear Time Algorithm for the Chamfer Distance
237. NeurIPS 2023Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
238. NeurIPS 2023Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
239. NeurIPS 2023Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction
240. NeurIPS 2023Non-adversarial training of Neural SDEs with signature kernel scores
241. NeurIPS 2023On the Constrained Time-Series Generation Problem
242. NeurIPS 2023On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails
243. NeurIPS 2023One Fits All: Power General Time Series Analysis by Pretrained LM
244. NeurIPS 2023OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
245. NeurIPS 2023PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection
246. NeurIPS 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space
247. NeurIPS 2023Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
248. NeurIPS 2023Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
249. NeurIPS 2023Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time
250. NeurIPS 2023RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing

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.