time-series-foundation-models/lag-llama
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
PythonApache-2.0
Stargazers
- 2187Nicknomad
- AlbertoLanaro@compiuta-origin
- ArianKhorasaniMila - Quebec Artificial Intelligence Institute
- ashok-arjunMontréal
- AtanasD
- bobo-jamsonTX
- carlosvilluDomestika.org
- ChristiaanWewer
- DSergiu
- EtienneT
- ferpapi-clear
- FiazAbrar
- gabrevayaUniversity of Buenos Aires
- GabruiInstituto Tecnológico de Aeronáutica
- gbaranyLondon
- george-adams1Montreal, Canada
- greefea
- HaukeHillebrandt
- ianspektor@BuenProvecho
- josephwinston
- leizhangtech
- LulzxAsia, Earth
- martins0n
- mat-ejPrague
- rasenganaiDubverse.ai
- rishika2110
- schallkoBerlin
- selcukakbasPepsiCo
- shchurBerlin, Germany
- shyamsn97
- shyamvalsan@netdata
- silentninjaCenter of Complex Interventions
- TimPchelintsev@108systems
- vvonchain
- YeasirRayhanPrincePurdue University
- ywx649999311Bishop's University