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Research map / Probabilistic and scientific modeling / Molecules and proteins

Inference in Higher Order MRF-MAP Problems With Small and Large Cliques

CVPR 2018 · Probabilistic and scientific modeling › Molecules and proteins · approach: Machine learning for physical simulation · 5 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the hybrid flow-based and polyhedral inference framework instead of SOSMNPMRF-MAP inference with mixed small and large cliques · Synthetic count-based cliques, 50×50 image; small clique 2×1runtime (seconds): 274.27 -> 11.54Helped
Use the hybrid flow-based and polyhedral inference framework instead of SOSMNPMRF-MAP inference with mixed small and large cliques · Synthetic edge-based cliques, 50×50 image; small clique 2×1runtime (seconds): 250.67 -> 17.41Helped
Use the hybrid flow-based and polyhedral inference framework instead of SOSMNPMRF-MAP inference with mixed small and large cliques · Synthetic count-based cliques; 2500 pixels, 40 big cliquesruntime (seconds): 295.73 -> 31.28Helped
Use the hybrid flow-based and polyhedral inference framework instead of SOSMNPMRF-MAP inference with mixed small and large cliques · Synthetic count-based cliques; 6400 pixels, 50 big cliquesruntime (seconds): 349.71 -> 32.50Helped
Increase the small-clique window size from 2×2 to 4×3HybridMNGC · Synthetic count-based cliques, 50×50 image; 25 big cliquesruntime (seconds): 9.42 -> 58.48Hurt
Increase the number of big cliques from 40 to 120HybridMNGC · Synthetic count-based cliques; 2500 pixelsruntime (seconds): 31.28 -> 94.66Hurt
Increase image size from 2500 to 6400 pixelsHybridMNGC · Synthetic count-based cliques; 50 big cliquesruntime (seconds): 34.69 -> 32.50Mixed
Combine small pairwise cliques with large region-level cliquesHybridMNGC object segmentation · Pascal VOC object segmentation with Gaussian noisesegmentation qualityHelped

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