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

757 papers, page 5 of 16

201. NeurIPS 2026RnR: a meta-solver for causal discovery in undersampled time series data
202. NeurIPS 2026Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization
203. NeurIPS 2026Robust Residual Correction via Selective Deployment for Time Series Forecasting
204. NeurIPS 2026Robust Stream Classification using Time Neutralising Decision Trees
205. NeurIPS 2026Rubato: Signature Attention for Irregular Multivariate Time Series Forecasting
206. NeurIPS 2026Runtime Analysis of Cartesian Genetic Programming on MAX: A Proven Exponential Speedup
207. NeurIPS 2026S3Former: Sequential, Structural, and Statistical Fusion for Continuous-Time Dynamic Graphs
208. NeurIPS 2026Safe Active Learning with Future Viability Guarantees in Time-Series Models
209. NeurIPS 2026SDFlow: Similarity-Driven Flow Matching for Time Series Generation
210. NeurIPS 2026SDHilb: Schrödinger Dynamics-Guided Neural Network with Adaptive Multi-Scale Hilbert Transform for Time Series Forecasting
211. NeurIPS 2026Self-Trained Verification for Training- and Test-Time Self-Improvement
212. NeurIPS 2026Semantically Complementary Spectral Views Learning for Graph-Level Anomaly Detection
213. NeurIPS 2026SetAD: Semi-Supervised Anomaly Learning in Contextual Sets
214. NeurIPS 2026SIGMA: A Sigmoid-Gated Sampler for Test-Time Scaling in Diffusion Language Models
215. NeurIPS 2026SLiDE: Structured Linear Dynamics for Forecasting with Exogenous Inputs
216. NeurIPS 2026SPECS: Faster Test-Time Scaling through Speculative Drafts and Dynamic Switching
217. NeurIPS 2026Spectral Energy Allocation Enables Source-Free Domain Adaptation in Time Series Forecasting
218. NeurIPS 2026Spectral Transformer Neural Processes
219. NeurIPS 2026Spikes as Detectors: Phase-Conditioned Spiking Dynamics for Time-Series Anomaly Detection
220. NeurIPS 2026SpikeSTAG: A Dendritic Compartmental Spiking Graph Network for Multivariate Time-Series Forecasting
221. NeurIPS 2026Stability-Weighted Direction Regularization Disentangles Generator Shortcuts from Detection Signal
222. NeurIPS 2026Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping
223. NeurIPS 2026Stable Alpha: Adversarial Invariant Representation Learning for Nonlinear Asset Pricing under Temporal Distribution Shifts
224. NeurIPS 2026Stable Resolution-Invariant Emulation in Entropically Controlled Kinetic Methods
225. NeurIPS 2026STAR: Boosting Time Series Foundation Models for Anomaly Detection Through State-Aware Adapter
226. NeurIPS 2026SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting
227. NeurIPS 2026STEP: Learning STructured Embeddings for Progressive Time Series
228. NeurIPS 2026Stochastic Approximation Approach for Decentralized Optimization on Time Varying Random Networks
229. NeurIPS 2026Strongly Adaptive Online Learning with Time-Varying Movement Cost
230. NeurIPS 2026Supervision Recovery for Time Series Anomaly Detection via Counterfactual Pairing
231. NeurIPS 2026TailFix: Mitigating Error Accumulation and Correcting Tail Deterioration in Long-Horizon Forecasting
232. NeurIPS 2026TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
233. NeurIPS 2026Temporal Island Sparse Autoencoders for Interpreting Clinical Time-Series Models
234. NeurIPS 2026Temporal-Scale Sensitivity in Time-Series Tokenization and Scale-Robust Token Estimation by Gated Sum
235. NeurIPS 2026TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection
236. NeurIPS 2026Test Time Search Requires Training for Diversity
237. NeurIPS 2026Test time training enhances in-context learning of nonlinear functions
238. NeurIPS 2026Test-Time Adaptation via Self-Reinforced Optimal Transport for Zero-Shot OOD Detection with Vision–Language Models
239. NeurIPS 2026Test-Time Compute Games
240. NeurIPS 2026Test-Time Conditioning with Representation-Aligned Visual Features
241. NeurIPS 2026Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
242. NeurIPS 2026Test-Time Graph Anomaly Detection via Shifted Augmentation with Dynamic Objective Scheduling
243. NeurIPS 2026Test-Time Learning with an Evolving Library
244. NeurIPS 2026Test-Time Prompt-Agnostic Decomposition
245. NeurIPS 2026Test-time Risk Adaptation with Mixture of Agents
246. NeurIPS 2026Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck
247. NeurIPS 2026Test-time Scaling of Diffusions with Flow Maps
248. NeurIPS 2026Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
249. NeurIPS 2026Test-Time Sequential Steering of Diffusion Models via Preconditioned Crank-Nicolson
250. NeurIPS 2026The BV4 Benchmark for Unsupervised Anomaly Detection in High-Dimensional Spectral Data Streams

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.