Research map / Probabilistic and scientific modeling / Variational and generative sampling
Unsupervised Learning with Contrastive Latent Variable Models
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use robust cLVM instead of cPCA with mean imputation | Mice protein expression · Mice protein expression, natural missingness and artificially increased missingness | subgroup discovery | Helped |
| Use robust cLVM instead of standard cLVM (ablation) | Synthetic data with outliers · Synthetic data with outliers | recovery of target latent representation | Helped |
| Add ARD for automatic selection of the shared latent dimension (ablation) | cLVM · Single-cell RNA-Seq | subgroup discovery | Helped |
| Add ARD for automatic selection of the shared latent dimension (ablation) | cLVM · Synthetic data with cluster-specific target latent means | shared-dimension selection | Helped |
| Add group sparsity regularization to the target factor loading (ablation) | cLVM · mHealth sensor data | feature selection | Helped |
| Use a horseshoe prior for the target factor loading (ablation) | cLVM · mHealth sensor data | feature selection | Helped |
| Use cVAE instead of a standard VAE with the same combined latent dimensionality | VAE · MNIST digits on grass | digit clustering in latent space | Helped |
| Use a two-dimensional target latent space and an eight-dimensional shared space to separate target and background structure (ablation) | cVAE · MNIST digits on grass | selective generation of target and background | Helped |
| Use cLVM instead of PCA | cLVM · Single-cell RNA-Seq | subgroup discovery | Helped |
| Use cLVM instead of PCA | cLVM · Mice protein expression | subgroup discovery | Helped |
| Set the shared latent dimension to zero (ablation) | cLVM · Synthetic data | contrastive latent structure | Mixed |
| Use a Student's t likelihood instead of a Gaussian likelihood (ablation) | cLVM · Synthetic data with outliers | recovery of target latent representation | Helped |
Closest papers by meaning
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- Latent variable model for high-dimensional point process with structured missingness (ICML 2024 · similarity 0.83)
- Machine Unlearning in Low-Dimensional Feature Subspace (NeurIPS 2026 · similarity 0.83)
- Learning Discrete Latent Variable Structures with Tensor Rank Conditions (NeurIPS 2024 · similarity 0.83)
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