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

298 papers, page 2 of 6

51. NeurIPS 2026Coordinating Hundreds of RL Agents through Scalable Inference-Time Search
52. NeurIPS 2026Counterfactual Explanations for Time-Series Classification via Constrained Flow Matching
53. NeurIPS 2026Crosscoding Through Time: Sparse Feature Discovery Across Sequence Positions
54. NeurIPS 2026CVTA: Cross-Variable Temporal Attention for Multivariate Irregular Time Series Prediction
55. NeurIPS 2026Cylindrical Geodesic Flow Matching for Quasiperiodic Physiological Signal Transformation
56. NeurIPS 2026Decomposing Temporal and Job-Induced Dynamics for Probabilistic Computing Workload Forecasting via Graph-Conditioned Dual-Branch Diffusion
57. NeurIPS 2026DEDCA: Test-Time Adaptation for Generalized AI-Generated Image Detection
58. NeurIPS 2026Deployment-Memory LLM Test-Time Training Should Require Behavioral Evidence Beyond Perplexity
59. NeurIPS 2026Deployment-Time Online Imitation Learning from Corrective Demonstrations
60. NeurIPS 2026DetectViT: Test-time Backdoor Detection for Vision Transformers via Inter-Head Attention Discrepancy
61. NeurIPS 2026Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting
62. NeurIPS 2026DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
63. NeurIPS 2026Diffusion-Time Concept Manifolds: Sparse Autoencoder Groups for Interpreting Denoising Language Models
64. NeurIPS 2026Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts
65. NeurIPS 2026Distillation of Foundation Models for Time-dependent PDEs
66. NeurIPS 2026Distilling Multi-Teacher Scoring Principles for Unsupervised Time Series Anomaly Detection
67. NeurIPS 2026Do Deep Networks Forget Initialization? A Forgetting-Time View of Practical Inductive Bias
68. NeurIPS 2026DoFP-Aligned Lookup Tables for Real-Time Polarization Demosaicking
69. NeurIPS 2026DSR-TSF: Spectrum-Driven Dynamic Routing for Efficient Long-Horizon Time Series Forecasting
70. NeurIPS 2026DSSNet: Deep Spectral Structure Profiling Network for Traffic Flow Prediction
71. NeurIPS 2026Dynamic Dual-Feedback Conformal Inference for Time Series Forecasting
72. NeurIPS 2026Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer
73. NeurIPS 2026DynaPFN: Zero-Shot Dynamical System Forecasting with Tabular Prior-Fitted Networks
74. NeurIPS 2026Early Signals, Strong Decisions: Prefix-Guided Sampling for Parallel Test-Time Scaling
75. NeurIPS 2026Echoes of Error: Residual-Directional Local Rollout Consistency for Timeseries Forecasting
76. NeurIPS 2026Empowering Time Series Analysis with Large-Scale Multimodal Pretraining
77. NeurIPS 2026Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach
78. NeurIPS 2026Entropy Guided Dynamic Patch Segmentation for Time Series Transformers
79. NeurIPS 2026ESENSC: A Polynomial-Time Axiomatic Alternative to SHAP
80. NeurIPS 2026EVA-0: Test-Time Model Evolution with Only Two Forward Passes per Sample
81. NeurIPS 2026Evaluating Deployable Inference-Time Error Prediction in Vision MoEs
82. NeurIPS 2026Evaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models
83. NeurIPS 2026EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales
84. NeurIPS 2026Exact Flow Linear Attention: Exact Solution from Continuous-Time Dynamics
85. NeurIPS 2026ExComm: Exploration-Stage Communication for Error-Resilient Agentic Test-Time Scaling
86. NeurIPS 2026FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization
87. NeurIPS 2026Fast-WAM: Do World Action Models Need Test-time Future Imagination?
88. NeurIPS 2026FASTER: Rethinking Real-Time Flow VLAs
89. NeurIPS 2026FENet: Functional Embedding Neural Network for Change-Point Detection in Functional Time Series
90. NeurIPS 2026fev-bench: A Realistic Benchmark for Time Series Forecasting
91. NeurIPS 2026Filter Banks: from Low-Rank Representations to Deep Models for Efficient Time Series Forecasting
92. NeurIPS 2026FIND: Frequency Invariance Disentanglement for Test-Time Adaptation in LiDAR 3D Detection
93. NeurIPS 2026Finite Time Analysis of Risk-Sensitive RL via Noisy Power Iteration
94. NeurIPS 2026First-Token Attraction in Mamba Dynamics
95. NeurIPS 2026FISC: Time-Series Forecasting via First-Layer Statistical Calibration Constraints
96. NeurIPS 2026FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
97. NeurIPS 2026Flow Matching from Viewpoint of Proximal Operators
98. NeurIPS 2026Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models
99. NeurIPS 2026Flow+Diff: Unifying Flow and Diffusion Representations for Multivariate Time Series Anomaly Detection
100. NeurIPS 2026Focus, Align, and Diffuse: Time-Series-Aware Keyframe Diffusion for Cardiac Dynamic Synthesis from Sparse Observations

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.