3 papers
cs.LG2026
Beyond Similarity: Temporal Operator Attention for Time Series Analysis
Jevon Twitty, Vinh Pham, Nitiwith Rotchanarak +4
A persistent paradox in time-series forecasting is that structurally simple MLP and linear models often outperform high-capacity Transformers. We argue that this gap arises from a…
cs.LG2026
StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
Yubin Kim, Viresh Pati, Jevon Twitty +3
Transformer architectures have established strong baselines in time series forecasting, yet they typically rely on positional encodings that assume uniform, index-based temporal pr…
cs.LG2026
CAPS: Unifying Attention, Recurrence, and Alignment in Transformer-based Time Series Forecasting
Viresh Pati, Yubin Kim, Vinh Pham +3
This paper presents (Clock-weighted Aggregation with Prefix-products and Softmax), a structured attention mechanism for time series forecasting that decouples three…