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 43 of 44

2101. NeurIPS 2023ForecastPFN: Synthetically-Trained Zero-Shot Forecasting
2102. NeurIPS 2023FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
2103. NeurIPS 2023Frequency-domain MLPs are More Effective Learners in Time Series Forecasting
2104. NeurIPS 2023Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time
2105. NeurIPS 2023Geometric Neural Diffusion Processes
2106. NeurIPS 2023GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
2107. NeurIPS 2023Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians
2108. NeurIPS 2023Granger Components Analysis: Unsupervised learning of latent temporal dependencies
2109. NeurIPS 2023GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
2110. NeurIPS 2023Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
2111. NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
2112. NeurIPS 2023Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
2113. NeurIPS 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
2114. NeurIPS 2023Large Language Models Are Zero-Shot Time Series Forecasters
2115. NeurIPS 2023Latent SDEs on Homogeneous Spaces
2116. NeurIPS 2023Linear Time Algorithms for k-means with Multi-Swap Local Search
2117. NeurIPS 2023Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction
2118. NeurIPS 2023MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection
2119. NeurIPS 2023Most Neural Networks Are Almost Learnable
2120. NeurIPS 2023Near-Linear Time Algorithm for the Chamfer Distance
2121. NeurIPS 2023Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression
2122. NeurIPS 2023Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling
2123. NeurIPS 2023Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction
2124. NeurIPS 2023Non-adversarial training of Neural SDEs with signature kernel scores
2125. NeurIPS 2023On the Constrained Time-Series Generation Problem
2126. NeurIPS 2023On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails
2127. NeurIPS 2023One Fits All: Power General Time Series Analysis by Pretrained LM
2128. NeurIPS 2023OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
2129. NeurIPS 2023PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection
2130. NeurIPS 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space
2131. NeurIPS 2023Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
2132. NeurIPS 2023Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
2133. NeurIPS 2023Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time
2134. NeurIPS 2023RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing
2135. NeurIPS 2023SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise
2136. NeurIPS 2023Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels
2137. NeurIPS 2023SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
2138. NeurIPS 2023SODA: Robust Training of Test-Time Data Adaptors
2139. NeurIPS 2023Sparse Graph Learning from Spatiotemporal Time Series
2140. NeurIPS 2023Survival Permanental Processes for Survival Analysis with Time-Varying Covariates
2141. NeurIPS 2023SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting
2142. NeurIPS 2023Taming Local Effects in Graph-based Spatiotemporal Forecasting
2143. NeurIPS 2023Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification
2144. NeurIPS 2023The noise level in linear regression with dependent data
2145. NeurIPS 2023Time Series as Images: Vision Transformer for Irregularly Sampled Time Series
2146. NeurIPS 2023Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings
2147. NeurIPS 2023Time-Independent Information-Theoretic Generalization Bounds for SGLD
2148. NeurIPS 2023Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value
2149. NeurIPS 2023Time-uniform confidence bands for the CDF under nonstationarity
2150. NeurIPS 2023Towards Optimal Effective Resistance Estimation

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.