2 papers
cs.LG2026
The Nixtlaverse: An Open-Source Ecosystem for Forecasting
Olivier Sprangers, Max Mergenthaler Canseco, Marco Peixeiro +8
Large forecasting applications often combine statistical, machine-learning, and neural models. These families solve the same problem but differ in fitted state, training procedures…
cs.LG2026
FedCausal-Dyn: A Causal-Dynamic Paradigm for Federated Learning under Dynamic Feature Drift
Kaijie Chen, Alex Johnson, Maria Garcia +2
This paper addresses the challenging problem of dynamic feature drift in federated learning, where data distributions evolve across clients and over time -- a common scenario in re…