TimeCHEAT combines local channel-dependent embedding via bipartite graph learning with global channel-independent Transformer encoding, beating or matching prior models on several irregularly sampled multivariate time series benchmarks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis
TimeCHEAT combines local channel-dependent embedding via bipartite graph learning with global channel-independent Transformer encoding, beating or matching prior models on several irregularly sampled multivariate time series benchmarks.