25 citations · 28 across the 4 of their papers we have counts for
5 papers
TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models
Martin Maritsch, Timo Stoffregen, Thomas Kaar +36
Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…
Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting
Azul Garza, Renée Rosillo, Rodrigo Mendoza-Smith +5
Recent advances in time-series forecasting increasingly rely on pre-trained foundation-style models. While these models often claim broad generalization, existing evaluation protoc…
TimeCopilot
Azul Garza, Renée Rosillo
We introduce TimeCopilot, the first open-source agentic framework for forecasting that combines multiple Time Series Foundation Models (TSFMs) with Large Language Models (LLMs) thr…
TimeGPT-1
Azul Garza, Cristian Challu, Max Mergenthaler-Canseco
In this paper, we introduce TimeGPT, the first foundation model for time series, capable of generating accurate predictions for diverse datasets not seen during training. We evalua…
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in Python
Kin G. Olivares, Azul Garza, David Luo +5
Large collections of time series data are commonly organized into structures with different levels of aggregation; examples include product and geographical groupings. It is often…