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DISCO Nets : DISsimilarity COefficients Networks

NeurIPS 2016 · Probabilistic and scientific modeling › Uncertainty and Gaussian processes · approach: Priors and functional variational uncertainty · 30 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace deterministic BASE (sigma=1) with DISCO gamma=0.5DISCO Nets · Hand pose estimation, test setProbLoss (mm): 103.8 -> 83.8Helped
replace BASE with DISCO gamma=0.5DISCO Nets · Hand pose estimation, test setMeJEE (mm): 25.2 -> 20.9Helped
replace BASE with DISCO gamma=0.5DISCO Nets · Hand pose estimation, test setFF (80mm): 86.040 -> 94.438Helped
increase BASE noise sigma from 1 to 10 (ablation)BASE · Hand pose estimation, test setProbLoss (mm): 103.8 -> 96.3Helped
increase BASE noise sigma from 1 to 10 (ablation)BASE · Hand pose estimation, test setMaJEE (mm): 52.7 -> 53.2Hurt
raise gamma from 0 to 0.5 (ablation)DISCO Nets · Hand pose estimation, test setProbLoss (mm): 92.9 -> 83.8Helped
raise gamma from 0 to 0.25 (ablation)DISCO Nets · Hand pose estimation, test setProbLoss (mm): 92.9 -> 89.9Helped
raise gamma from 0.25 to 0.5 (ablation)DISCO Nets · Hand pose estimation, test setMaJEE (mm): 46.4 -> 45.1Helped
all-zero noise at test time (ablation)DISCO Nets · Hand pose estimation, test setpointwise metrics (MeJEE, MaJEE)No clear effect
random init instead of DISCO-initialised fixed conv layers for cGAN (ablation)cGAN · Hand pose estimation, test setProbLoss (mm): 128.9 -> 442.7Hurt
cGAN init fixed vs DISCO gamma=0.5cGAN init, fixed · Hand pose estimation, test setProbLoss (mm): 83.8 -> 128.9Hurt
train loss differs from task loss (toy Gaussian example) (ablation)Gaussian fit · Mixture of Gaussians toyDelta_A task loss: 13.7 -> 11.6Helped

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