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

875 papers, page 17 of 18

801. NeurIPS 2026Stable Resolution-Invariant Emulation in Entropically Controlled Kinetic Methods
802. NeurIPS 2026STAR: Boosting Time Series Foundation Models for Anomaly Detection Through State-Aware Adapter
803. NeurIPS 2026SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting
804. NeurIPS 2026STEP: Learning STructured Embeddings for Progressive Time Series
805. NeurIPS 2026Stochastic Approximation Approach for Decentralized Optimization on Time Varying Random Networks
806. NeurIPS 2026Strongly Adaptive Online Learning with Time-Varying Movement Cost
807. NeurIPS 2026Supervision Recovery for Time Series Anomaly Detection via Counterfactual Pairing
808. NeurIPS 2026TailFix: Mitigating Error Accumulation and Correcting Tail Deterioration in Long-Horizon Forecasting
809. NeurIPS 2026TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
810. NeurIPS 2026Temporal Island Sparse Autoencoders for Interpreting Clinical Time-Series Models
811. NeurIPS 2026Temporal-Scale Sensitivity in Time-Series Tokenization and Scale-Robust Token Estimation by Gated Sum
812. NeurIPS 2026TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection
813. NeurIPS 2026Test Time Search Requires Training for Diversity
814. NeurIPS 2026Test time training enhances in-context learning of nonlinear functions
815. NeurIPS 2026Test-Time Adaptation via Self-Reinforced Optimal Transport for Zero-Shot OOD Detection with Vision–Language Models
816. NeurIPS 2026Test-Time Compute Games
817. NeurIPS 2026Test-Time Conditioning with Representation-Aligned Visual Features
818. NeurIPS 2026Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
819. NeurIPS 2026Test-Time Graph Anomaly Detection via Shifted Augmentation with Dynamic Objective Scheduling
820. NeurIPS 2026Test-Time Learning with an Evolving Library
821. NeurIPS 2026Test-Time Prompt-Agnostic Decomposition
822. NeurIPS 2026Test-time Risk Adaptation with Mixture of Agents
823. NeurIPS 2026Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck
824. NeurIPS 2026Test-time Scaling of Diffusions with Flow Maps
825. NeurIPS 2026Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
826. NeurIPS 2026Test-Time Sequential Steering of Diffusion Models via Preconditioned Crank-Nicolson
827. NeurIPS 2026The BV4 Benchmark for Unsupervised Anomaly Detection in High-Dimensional Spectral Data Streams
828. NeurIPS 2026The sublevel Flood bifiltration: towards scalable 2-parameter persistent homology
829. NeurIPS 2026TIDES: Implicit Time-Awareness in Selective State Space Models
830. NeurIPS 2026Time series analysis with Gumbel dynamics
831. NeurIPS 2026Time-Frequency Decoupled Cross-Scale Partial Optimal Transport for Time Series Domain Adaptation
832. NeurIPS 2026Time–Frequency Non-Stationary Modeling for Multivariate Time Series Forecasting
833. NeurIPS 2026TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning
834. NeurIPS 2026TimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectra
835. NeurIPS 2026TimeOperator: A Function-to-Function Approach to Time Series Modeling
836. NeurIPS 2026TimeTok: Granularity-Controllable Time-Series Generation via Hierarchical Tokenization
837. NeurIPS 2026Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection
838. NeurIPS 2026To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
839. NeurIPS 2026TokenCLIP: Token-wise Prompt Learning for Zero-shot Anomaly Detection
840. NeurIPS 2026Tokenization and Architecture Jointly Allocate Component Roles in Time Series Transformers
841. NeurIPS 2026ToLD: Efficient Time Series Forecasting via Tokenized Truncated Latent Diffusion
842. NeurIPS 2026Tool Verification for Test-Time Reinforcement Learning
843. NeurIPS 2026Topological Periodicity Test (TopPT) via Confidence Bound of Time-Delay Embeddings
844. NeurIPS 2026Topology-Aware Optimal Transport for Source-Free Test-Time Adaptation in Anomaly Segmentation
845. NeurIPS 2026Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time
846. NeurIPS 2026Towards Generalist Graph-Level Anomaly Detection
847. NeurIPS 2026Towards Principled Efficient Rollout Allocation in Test-Time Training
848. NeurIPS 2026Training Agent to Scale Inference-Time Reasoning
849. NeurIPS 2026Training Quality Determines Efficiency Boundaries in Test-Time Reasoning
850. NeurIPS 2026Training-Free Cultural Alignment of Large Language Models via Persona Disagreement

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.