Pages that link to "Item:Q5234401"
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The following pages link to Approximate Bayesian Computation with the Wasserstein Distance (Q5234401):
Displaying 30 items.
- Dependence properties and Bayesian inference for asymmetric multivariate copulas (Q2008218) (← links)
- Distance-learning for approximate Bayesian computation to model a volcanic eruption (Q2040676) (← links)
- Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors (Q2080374) (← links)
- Limitations of the Wasserstein MDE for univariate data (Q2103964) (← links)
- Wasserstein statistics in one-dimensional location-scale models (Q2117890) (← links)
- Weighted approximate Bayesian computation via Sanov's theorem (Q2135932) (← links)
- Minimax confidence intervals for the sliced Wasserstein distance (Q2137795) (← links)
- A comparison of likelihood-free methods with and without summary statistics (Q2141917) (← links)
- Likelihood-free inference with deep Gaussian processes (Q2157533) (← links)
- Using space filling curves to compare two multivariate distributions with distribution-free tests (Q2161060) (← links)
- Posterior asymptotics in Wasserstein metrics on the real line (Q2233550) (← links)
- Approximate Bayesian computations to fit and compare insurance loss models (Q2234770) (← links)
- Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs (Q2302513) (← links)
- On parameter estimation with the Wasserstein distance (Q5006506) (← links)
- Optimal Transport to a Variety (Q5014695) (← links)
- (Q5054639) (← links)
- Projected Wasserstein Gradient Descent for High-Dimensional Bayesian Inference (Q5880609) (← links)
- GAT–GMM: Generative Adversarial Training for Gaussian Mixture Models (Q5885836) (← links)
- Sequential Monte Carlo samplers to fit and compare insurance loss models (Q6096074) (← links)
- Discrepancy-based inference for intractable generative models using quasi-Monte Carlo (Q6158226) (← links)
- Unsupervised mixture estimation via approximate maximum likelihood based on the Cramér-von Mises distance (Q6170532) (← links)
- On predictive inference for intractable models via approximate Bayesian computation (Q6171773) (← links)
- Convergence rates for ansatz‐free data‐driven inference in physically constrained problems (Q6188899) (← links)
- Approximating Bayes in the 21st century (Q6540227) (← links)
- Black-box Bayesian inference for agent-based models (Q6567092) (← links)
- Approximate Bayesian computation via classification (Q6582883) (← links)
- The distance between: an algorithmic approach to comparing stochastic models to time-series data (Q6601321) (← links)
- Calibration of stochastic, agent-based neuron growth models with approximate Bayesian computation (Q6622628) (← links)
- Generalized Bayesian likelihood-free inference (Q6635569) (← links)
- Statistical inference with regularized optimal transport (Q6663353) (← links)
