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

599 papers, page 3 of 12

101. ICML 2026Geometrically Constrained Outlier Synthesis
102. ICML 2026Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition
103. ICML 2026GEPC: Group-Equivariant Posterior Consistency for Out-of-Distribution Detection in Diffusion Models
104. ICML 2026GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
105. ICML 2026GHOST: Unmasking Phantom States in Mamba2 via Grouped Hidden-state Output-aware Selection & Truncation
106. ICML 2026Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
107. ICML 2026GradientStabilizer: Fix the Norm, Not the Gradient
108. ICML 2026HARD-KV: Head-Adaptive Regularization for Decoding-time KV Compression
109. ICML 2026HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation
110. ICML 2026Hi-Time: Hierarchical Latent Prediction for Multivariate Time Series Classification
111. ICML 2026Hierarchical ODE: Learning Continuous-Time Physical Prototypes for Early Link Failure Detection
112. ICML 2026HiPPO Zoo: Explicit Memory Mechanisms for Interpretable State Space Models
113. ICML 2026HSMAD: Heterophily-Driven Spectral and Manifold Learning for Graph Anomaly Detection
114. ICML 2026Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families
115. ICML 2026IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
116. ICML 2026Inference Time Optimization with Confidence Dynamics
117. ICML 2026Inference-time Alignment with Rewards in Besov Spaces: Provable Advantages of Feature Learning and Multi-Step Policy Updates
118. ICML 2026Information Geometry Loss for Time Series Forecasting
119. ICML 2026Interpretable Functional Koopman Learning with Non-Markovian Closure for Spatiotemporal Systems
120. ICML 2026Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising
121. ICML 2026It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
122. ICML 2026KineFlow: Kinematic Second-Order Flow Matching for Time-Series Forecasting
123. ICML 2026KITE: Knowledge-Guided Probabilistic Modeling for Time Series Forecasting with Exogenous Variables
124. ICML 2026KUMA: A Novel Framework with Koopman Separation and Efficient Multilevel Extraction in Time Series Forecasting
125. ICML 2026L-Drive: Beyond a Single Mapping—Latent Context Drives Time Series Forecasting
126. ICML 2026LagLLM: LLM-empowered lead–lag dependency learning for spatial-temporal time series forecasting
127. ICML 2026Laplacian Representations for Decision-Time Planning
128. ICML 2026Large Language Models Explore by Latent Distilling
129. ICML 2026Latent Laplace Diffusion for Irregular Multivariate Time Series
130. ICML 2026Learning Cardiac Latent Representations in Vectorcardiogram Space
131. ICML 2026Learning Coupled Continuous-Time Latent Dynamics from Irregular Events
132. ICML 2026Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
133. ICML 2026Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
134. ICML 2026Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
135. ICML 2026Learning Manifold and Itô Dynamics with Branched Neural Rough Differential Equations
136. ICML 2026Learning to Discover at Test Time
137. ICML 2026Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models
138. ICML 2026Mantis: Lightweight Foundation Model for Time Series Classification
139. ICML 2026MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification
140. ICML 2026MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
141. ICML 2026Memory-Distilled Selection for Noise-Robust Anomaly Detection
142. ICML 2026Mesh Field Theory: Port–Hamiltonian Formulation of Mesh-Based Physics
143. ICML 2026Meta Flow Maps enable scalable reward alignment
144. ICML 2026Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments
145. ICML 2026MIMOMamba: From Scalar Duality to Matrix-Valued Attention
146. ICML 2026Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment
147. ICML 2026Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
148. ICML 2026MoRGen: Mixture-of-Resolutions Generative Forecasting for Irregularly Sampled Medical Time-Series Data
149. ICML 2026MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
150. ICML 2026Multi-Integration of Labels Across Categories for Component Identification in Multi-trial Time Series

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.