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Gaussian mixture

Benchmarks

Task Name	Dataset Name	SOTA Result
Discrete-space EOT/SB solving	High-dimensional Gaussian Mixture	Conditional Shape Score95	21
Sampling diversity and quality estimation	Gaussian mixture	Mode Coverage (Marginal)6.53	17
Balanced Linear Optimal Transport	Gaussian-mixture n=m=10k R2	f/f* Ratio1	12
Anomaly Detection	Gaussian Mixture Local Anomalies (synthetic)	AUCROC99.19	12
Posterior Estimation	Gaussian-Mixture	Area of HPD Region7.972	10
Anomaly Detection	Gaussian mixture local anomalies synthetic (test)	F1 Score89.37	10
Simulation-Based Inference	Gaussian Mixture	Computation Time (s)0.01	8
Expectation estimation	Gaussian mixture (test)	Jensen-Shannon Divergence0.044	7
Simulation-Based Inference	Gaussian Mixture	C2ST Accuracy56	7
Principal Component Alignment	Gaussian Mixture ($d=900, n=10^3, \pi_1=20\%)	Alignment (%)96.17	7
Principal Component Alignment	Gaussian Mixture ($d=900, n=10^3, \pi_1=15\%$)	PCA Alignment97.39	7
Principal Component Alignment	Gaussian Mixture ($d=900, n=10^3, \pi_1=10\%$)	Alignment97.16	7
Principal Component Alignment	Gaussian Mixture ($d=900, n=10^3, \pi_1=5\%$)	Alignment (%)95.85	7
Posterior Sampling	Gaussian Mixture SBI benchmark	C2ST96	7
Sample Quality Evaluation	Gaussian Mixture (GM)	MMD0.1576	6
Normalizing Constant Estimation	Gaussian Mixture (GM)	Ratio Z_hat / Z1.0001	6
Importance-weight estimation	Gaussian mixture (test)	Squared Error2.6	5
Posterior sampling	four-dimensional Gaussian mixture (test)	Expected Distance (ED)0.0958	5
Feature Selection	Gaussian mixture n=2000 p=100	FDR Mean0.081	5
Feature Selection	Gaussian mixture p=100 (n=200)	FDR Mean0.116	5
Misclassification Risk Estimation	Gaussian Mixture Example 1	Expectile Misclassification Risk (τ=0.99)0.3799	4
Resampling	Gaussian mixture (test)	Metric-	0
Source distribution estimation	Gaussian Mixture (GM)	Metric-	0

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