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 4 of 6

151. ICML 2023Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
152. ICML 2023Neural Stochastic Differential Games for Time-series Analysis
153. ICML 2023Non-autoregressive Conditional Diffusion Models for Time Series Prediction
154. ICML 2023Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think
155. ICML 2023Nonparametric Density Estimation under Distribution Drift
156. ICML 2023ODS: Test-Time Adaptation in the Presence of Open-World Data Shift
157. ICML 2023On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing
158. ICML 2023On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network
159. ICML 2023On Pitfalls of Test-Time Adaptation
160. ICML 2023On the Statistical Benefits of Temporal Difference Learning
161. ICML 2023On the Stepwise Nature of Self-Supervised Learning
162. ICML 2023Optimal LP Rounding and Linear-Time Approximation Algorithms for Clustering Edge-Colored Hypergraphs
163. ICML 2023Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
164. ICML 2023Predicting Ordinary Differential Equations with Transformers
165. ICML 2023Probabilistic Imputation for Time-series Classification with Missing Data
166. ICML 2023Prototype-oriented unsupervised anomaly detection for multivariate time series
167. ICML 2023Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
168. ICML 2023Regularization-free Diffeomorphic Temporal Alignment Nets
169. ICML 2023Safe Offline Reinforcement Learning with Real-Time Budget Constraints
170. ICML 2023Self-Interpretable Time Series Prediction with Counterfactual Explanations
171. ICML 2023Sequential Monte Carlo Learning for Time Series Structure Discovery
172. ICML 2023Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series
173. ICML 2023Sequential Predictive Conformal Inference for Time Series
174. ICML 2023SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
175. ICML 2023Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
176. ICML 2023Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization
177. ICML 2023The Fast Johnson-Lindenstrauss Transform Is Even Faster
178. ICML 2023Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
179. ICML 2023TIDE: Time Derivative Diffusion for Deep Learning on Graphs
180. ICML 2023Topological Singularity Detection at Multiple Scales
181. ICML 2023Uncovering Adversarial Risks of Test-Time Adaptation
182. NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
183. NeurIPS 2023Active Observing in Continuous-time Control
184. NeurIPS 2023Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
185. NeurIPS 2023Adaptive Test-Time Personalization for Federated Learning
186. NeurIPS 2023Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
187. NeurIPS 2023ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation
188. NeurIPS 2023Bandit Task Assignment with Unknown Processing Time
189. NeurIPS 2023BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
190. NeurIPS 2023Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability
191. NeurIPS 2023Bifurcations and loss jumps in RNN training
192. NeurIPS 2023BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series
193. NeurIPS 2023BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
194. NeurIPS 2023Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing
195. NeurIPS 2023Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
196. NeurIPS 2023Cal-DETR: Calibrated Detection Transformer
197. NeurIPS 2023Causal Discovery from Subsampled Time Series with Proxy Variables
198. NeurIPS 2023Causal Discovery in Semi-Stationary Time Series
199. NeurIPS 2023Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker
200. NeurIPS 2023Conformal PID Control for 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.