3 citations · 4 across the 3 of their papers we have counts for
3 papers
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift
Luca Masserano, Syama Sundar Rangapuram, Shubham Kapoor +3
The world is not static: This causes real-world time series to change over time through external, and potentially disruptive, events such as macroeconomic cycles or the COVID-19 pa…
Resilient Neural Forecasting Systems
Michael Bohlke-Schneider, Shubham Kapoor, Tim Januschowski
Industrial machine learning systems face data challenges that are often under-explored in the academic literature. Common data challenges are data distribution shifts, missing valu…
Bootstrapping NLU Models with Multi-task Learning
Shubham Kapoor, Caglar Tirkaz
Bootstrapping natural language understanding (NLU) systems with minimal training data is a fundamental challenge of extending digital assistants like Alexa and Siri to a new langua…