Multi-Channel Signal Transformers
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Related Articles from SNS
An Empirical Audit of Input Encoders for Multi-Channel Signal Transformers
arXiv:2606.04752v2 Announce Type: replace Abstract: Transformers consuming multi-channel scalar signals must embed $C$ simultaneous values into one $d_{\text{model}}$-dimensional vector per time step. We audit eight input encoders -- a shared-scalar baseline, per-channel linear projections, an orthogonality regulariser, a nonlinear MLP, block-partitioned concatenation, channel-independent and channel-as-token architectures, and a projected positional encoding -- on a synthetic benchmark...
An Empirical Audit of Input Encoders for Multi-Channel Signal Transformers
Announce Type: new Abstract: Transformers consuming multi-channel scalar signals must embed $C$ simultaneous values into one $d_{\text{model}}$-dimensional vector per time step. We empirically audit eight input encoders -- spanning a shared-scalar baseline, per-channel linear projections, an orthogonality regulariser, a nonlinear MLP stem, block-partitioned concatenation, channel-independent and channel-as-token architectures, and a projected positional encoding -- on a synthetic benchmark...
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