Neural Operator Processes (NOPs) unify neural-process conditioning with neural-operator decoding for probabilistic full-field prediction from sparse joint input-output observations.
Chelsea Finn, Pieter Abbeel, and Sergey Levine
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Neural Operator Processes for Probabilistic Operator Learning under Partial Observations
Neural Operator Processes (NOPs) unify neural-process conditioning with neural-operator decoding for probabilistic full-field prediction from sparse joint input-output observations.