Disentangling Computation in Multi-Task Neural Networks with the Green's Operator
Researchers use the Green's operator to map how multitask recurrent networks reuse computation across tasks and time.
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Researchers use the Green's operator to map how multitask recurrent networks reuse computation across tasks and time.
Researchers show repulsive self-attention in a minimal recurrent transformer produces chaos, condensation, and emergent locality.
Study shows nested-window Bi-LSTM architectures do not improve faster-than-Nyquist detection; pre-whitening plus BCJR distillation cuts bit error rates.
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