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Extracting Semantic-Dynamic Features for Long-Term Stable Brain Computer Interface

AAAI 2023 · Probabilistic and scientific modeling › Dynamical systems · approach: Latent-space control and planning · 3 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add joint-distribution alignment to SD-Net (ablation)SD-Net · CHEWIE D2R2: 0.773 -> 0.883Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · CHEWIE D3R2: 0.725 -> 0.933Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · CHEWIE D2accuracy: 0.859 -> 0.811Hurt
add joint-distribution alignment to SD-Net (ablation)SD-Net · CHEWIE D3accuracy: 0.747 -> 0.810Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · Jango D2R2: 0.43 -> 0.763Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · Jango D2accuracy: 0.75 -> 0.975Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · Jango D3R2: 0.438 -> 0.749Helped
add joint-distribution alignment to SD-Net (ablation)SD-Net · Jango D4accuracy: 0.49 -> 0.8Helped
align target features (ablation)SD-Net · simulated neuron deathaccuracy: 0.755 -> 0.865Helped
align target features (ablation)SD-Net · simulated electrode/tissue shiftaccuracy: 0.050 -> 0.839Helped
align target features (ablation)SD-Net · simulated tuning function changesaccuracy: −0.017 -> 0.838Helped
align target features (ablation)SD-Net · simulated combined shiftsaccuracy: 0.123 -> 0.779Helped

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