Imagen de Portada

ITGPT: Generative Pretraining on Irregular Timeseries

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Honoré, Antoine, Xiao, Ming
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Matrix Variational Auto-Encoder for Variant Effect Prediction in Pharmacogenes
por: Honoré, Antoine, et al.
Publicado: (2025)

DANSE: Data-driven Non-linear State Estimation of Model-free Process in Unsupervised Learning Setup
por: Ghosh, Anubhab, et al.
Publicado: (2023)

Operator Flow Matching for Timeseries Forecasting
por: Lee, Yolanne Yi Ran, et al.
Publicado: (2025)

There is No "apple" in Timeseries: Rethinking TSFM through the Lens of Invariance
por: Prabowo, Arian, et al.
Publicado: (2025)

Generating Expressive and Customizable Evals for Timeseries Data Analysis Agents with AgentFuel
por: Maddi, Aadyaa, et al.
Publicado: (2026)

Fine-tuning Timeseries Predictors Using Reinforcement Learning
por: Cazaux, Hugo, et al.
Publicado: (2026)

BTS: Building Timeseries Dataset: Empowering Large-Scale Building Analytics
por: Prabowo, Arian, et al.
Publicado: (2024)

Causality by Abstraction: Symbolic Rule Learning in Multivariate Timeseries with Large Language Models
por: Biswas, Preetom, et al.
Publicado: (2026)

Comparing Prior and Learned Time Representations in Transformer Models of Timeseries
por: Koliou, Natalia, et al.
Publicado: (2024)

Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns
por: De Rosa, Pasquale, et al.
Publicado: (2024)

Timeseries Foundation Models for Mobility: A Benchmark Comparison with Traditional and Deep Learning Models
por: Graser, Anita
Publicado: (2025)

Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition
por: Bouchabou, Damien, et al.
Publicado: (2024)

S2DEVFMAP: Self-Supervised Learning Framework with Dual Ensemble Voting Fusion for Maximizing Anomaly Prediction in Timeseries
por: Naidu, Sarala, et al.
Publicado: (2024)

Uncovering Memorization in Timeseries Imputation models: LBRM Membership Inference and its link to attribute Leakage
por: Taleb, Faiz, et al.
Publicado: (2026)

maneuverRecognition -- A Python package for Timeseries Classification in the domain of Vehicle Telematics
por: Schuster, Jonathan, et al.
Publicado: (2025)

Balancing Symmetry and Efficiency in Graph Flow Matching
por: Honoré, Benjamin, et al.
Publicado: (2026)

On the Generalization Ability of Unsupervised Pretraining
por: Deng, Yuyang, et al.
Publicado: (2024)

Limits of Generative Pre-Training in Structured EMR Trajectories with Irregular Sampling
por: Kuo, Nicholas I-Hsien, et al.
Publicado: (2025)

TSGM: Regular and Irregular Time-series Generation using Score-based Generative Models
por: Lim, Haksoo, et al.
Publicado: (2025)

Causal Discovery for Irregularly Time Series with Consistency Guarantees
por: Li, Weihong, et al.
Publicado: (2025)

Nexus: Same Pretraining Loss, Better Downstream Generalization via Common Minima
por: Chen, Huanran, et al.
Publicado: (2026)

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting
por: Rezaei, Mohammad R., et al.
Publicado: (2026)

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
por: Naiman, Ilan, et al.
Publicado: (2023)

Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
por: Chen, Panqi, et al.
Publicado: (2025)

General Intelligence Requires Reward-based Pretraining
por: Han, Seungwook, et al.
Publicado: (2025)

Dual-Label Learning With Irregularly Present Labels
por: Li, Mingqian, et al.
Publicado: (2024)

DeepConvContext: A Multi-Scale Approach to Timeseries Classification in Human Activity Recognition
por: Bock, Marius, et al.
Publicado: (2025)

A Diffusion Model for Regular Time Series Generation from Irregular Data with Completion and Masking
por: Fadlon, Gal, et al.
Publicado: (2025)

Generative Pretrained Hierarchical Transformer for Time Series Forecasting
por: Liu, Zhiding, et al.
Publicado: (2024)

Pretraining Scaling Laws for Generative Evaluations of Language Models
por: Schaeffer, Rylan, et al.
Publicado: (2025)

Safety Pretraining: Toward the Next Generation of Safe AI
por: Maini, Pratyush, et al.
Publicado: (2025)

Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
por: Serrano, Louis, et al.
Publicado: (2024)

Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
por: Pandey, Mohit, et al.
Publicado: (2025)

Revisiting Multilingual Data Mixtures in Language Model Pretraining
por: Foroutan, Negar, et al.
Publicado: (2025)

Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models
por: Xue, Shuchen, et al.
Publicado: (2025)

Enhancing compact convolutional transformers with super attention
por: Leandre, Simpenzwe Honore, et al.
Publicado: (2025)

Generalized Hierarchical Bayesian Segmentation with Irregular Designs, Multi-Sequence Hierarchies, and Grouped/Latent-Group Designs
por: Solari, Omid Shams
Publicado: (2026)

Probabilistic Circuits for Irregular Multivariate Time Series Forecasting
por: Klötergens, Christian, et al.
Publicado: (2026)

Valid and Expressive Copulas for Irregular Multivariate Time Series
por: Klötergens, Christian, et al.
Publicado: (2026)

Temporal Graph ODEs for Irregularly-Sampled Time Series
por: Gravina, Alessio, et al.
Publicado: (2024)