163 citations · 589 across the 42 of their papers we have counts for
18 papers · 1 filter
Multi-Task Learning for Budbreak Prediction
Aseem Saxena, Paola Pesantez-Cabrera, Rohan Ballapragada +2
Grapevine budbreak is a key phenological stage of seasonal development, which serves as a signal for the onset of active growth. This is also when grape plants are most vulnerable…
Grape Cold Hardiness Prediction via Multi-Task Learning
Aseem Saxena, Paola Pesantez-Cabrera, Rohan Ballapragada +3
Cold temperatures during fall and spring have the potential to cause frost damage to grapevines and other fruit plants, which can significantly decrease harvest yields. To help pre…
Offline Policy Comparison with Confidence: Benchmarks and Baselines
Anurag Koul, Mariano Phielipp, Alan Fern
Decision makers often wish to use offline historical data to compare sequential-action policies at various world states. Importantly, computational tools should produce confidence…
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results
Mohamad H Danesh, Alan Fern
We study the problem of out-of-distribution dynamics (OODD) detection, which involves detecting when the dynamics of a temporal process change compared to the training-distribution…
Piecewise-constant Neural ODEs
Sam Greydanus, Stefan Lee, Alan Fern
Neural networks are a popular tool for modeling sequential data but they generally do not treat time as a continuous variable. Neural ODEs represent an important exception: they pa…
Deep Convolution for Irregularly Sampled Temporal Point Clouds
Erich Merrill, Stefan Lee, Li Fuxin +2
We consider the problem of modeling the dynamics of continuous spatial-temporal processes represented by irregular samples through both space and time. Such processes occur in sens…