Temporal Operator Attention augments softmax attention with learnable sequence-space operators for signed temporal mixing and uses stochastic regularization to enable practical training, yielding consistent gains on time series benchmarks.
Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting
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
-
Beyond Similarity: Temporal Operator Attention for Time Series Analysis
Temporal Operator Attention augments softmax attention with learnable sequence-space operators for signed temporal mixing and uses stochastic regularization to enable practical training, yielding consistent gains on time series benchmarks.