Lindblad-inspired multi-timescale reservoir computing with separable rotation and dissipation
Read the original at arxiv.org→arXiv:2608.04028v1 Announce Type: new Abstract: Echo-state networks enable efficient temporal learning by fixing the recurrent dynamics and training only a linear readout. However, conventional reservoirs typically...
Original headline: "Lindblad-Inspired Multi-Timescale Reservoir Computing with Separable Rotation and Dissipation"
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- Aug 6, 04:00 UTC arXiv cs.LG lead source Lindblad-Inspired Multi-Timescale Reservoir Computing with Separable Rotation and Dissipation