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 13 of 44

601. NeurIPS 2026Beyond Normal References: Discriminative Few-Shot Anomaly Detection
602. NeurIPS 2026Beyond Single-Shot Conditioning: Test-Time Condition Refinement for Diffusion-Based Image Restoration
603. NeurIPS 2026Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
604. NeurIPS 2026Beyond Training Time, Test-Time Coordination is Essential for Cooperative MARL
605. NeurIPS 2026Beyond Truthfulness: Evaluating Honesty in Large Language Models
606. NeurIPS 2026Bridging Diffusion and Autoregression for Flexible Time Series Synthesis
607. NeurIPS 2026BucpTSF: Breaking the Uniform Computation Paradigm in Time-Series Forecasting
608. NeurIPS 2026C3VD-DEFCOL: A Deformable Colonoscopy Dataset with Time-Resolved 3D Ground Truth and Realistic Appearance
609. NeurIPS 2026CA-Judge: Teach Large Models to Judge Anomalies via Comparison for Video Anomaly Detection
610. NeurIPS 2026Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
611. NeurIPS 2026CAST: Causal Anchored Simplex Transport for Distribution-Valued Time Series
612. NeurIPS 2026Causal Discovery under Time-Varying Delays
613. NeurIPS 2026CCTimeBoost: Learning Time-Varying Relative Risk with Case-Control Boosted Trees
614. NeurIPS 2026CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling
615. NeurIPS 2026ClinStab: Stability-Oriented Learning for Medical Time Series via Dual-Stream Alignment
616. NeurIPS 2026CodeScaler: Scaling Code LLM Training and Test-Time Inference via Reward Models
617. NeurIPS 2026CoLaX: Context-Aware Local Explanations for Time Series Classification
618. NeurIPS 2026Colour me shocked: Exact Molecular Hessians from MLIPs in O(N) time using sparse differentiation!
619. NeurIPS 2026Combating Camouflage and Forgetting: Spatio-Temporal Dual Denoising for Money Laundering Detection
620. NeurIPS 2026COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection
621. NeurIPS 2026Component-Based Out-of-Distribution Detection
622. NeurIPS 2026Compute Aligned Training: Optimizing for Test Time Inference
623. NeurIPS 2026Conformal Prediction for Time-Dependent PDEs
624. NeurIPS 2026Conservative Continuous-Time Treatment Optimization
625. NeurIPS 2026Consilience for Verifier-Free Test-Time Scaling
626. NeurIPS 2026Continuous-Time Distribution Matching for Few-Step Diffusion Distillation
627. NeurIPS 2026Controlling Temporal Pseudo-Label Marginals for Stable Online Test-Time Adaptation
628. NeurIPS 2026Coordinating Hundreds of RL Agents through Scalable Inference-Time Search
629. NeurIPS 2026Counterfactual Explanations for Time-Series Classification via Constrained Flow Matching
630. NeurIPS 2026Crosscoding Through Time: Sparse Feature Discovery Across Sequence Positions
631. NeurIPS 2026CVTA: Cross-Variable Temporal Attention for Multivariate Irregular Time Series Prediction
632. NeurIPS 2026Cylindrical Geodesic Flow Matching for Quasiperiodic Physiological Signal Transformation
633. NeurIPS 2026Decomposing Temporal and Job-Induced Dynamics for Probabilistic Computing Workload Forecasting via Graph-Conditioned Dual-Branch Diffusion
634. NeurIPS 2026DEDCA: Test-Time Adaptation for Generalized AI-Generated Image Detection
635. NeurIPS 2026Deployment-Memory LLM Test-Time Training Should Require Behavioral Evidence Beyond Perplexity
636. NeurIPS 2026Deployment-Time Online Imitation Learning from Corrective Demonstrations
637. NeurIPS 2026DetectViT: Test-time Backdoor Detection for Vision Transformers via Inter-Head Attention Discrepancy
638. NeurIPS 2026Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting
639. NeurIPS 2026DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
640. NeurIPS 2026Diffusion-Time Concept Manifolds: Sparse Autoencoder Groups for Interpreting Denoising Language Models
641. NeurIPS 2026Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts
642. NeurIPS 2026Distillation of Foundation Models for Time-dependent PDEs
643. NeurIPS 2026Distilling Multi-Teacher Scoring Principles for Unsupervised Time Series Anomaly Detection
644. NeurIPS 2026Do Deep Networks Forget Initialization? A Forgetting-Time View of Practical Inductive Bias
645. NeurIPS 2026DoFP-Aligned Lookup Tables for Real-Time Polarization Demosaicking
646. NeurIPS 2026DSR-TSF: Spectrum-Driven Dynamic Routing for Efficient Long-Horizon Time Series Forecasting
647. NeurIPS 2026DSSNet: Deep Spectral Structure Profiling Network for Traffic Flow Prediction
648. NeurIPS 2026Dynamic Dual-Feedback Conformal Inference for Time Series Forecasting
649. NeurIPS 2026Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer
650. NeurIPS 2026DynaPFN: Zero-Shot Dynamical System Forecasting with Tabular Prior-Fitted Networks

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.