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Found 5 papers, 0 papers with code
Discovering Mixtures of Structural Causal Models from Time Series Data
In this work, we relax this assumption and perform causal discovery from time series data originating from a mixture of causal models.
Generalization on Unseen Domains via Inference-Time Label-Preserving Target Projections
Generalization of machine learning models trained on a set of source domains on unseen target domains with different statistics, is a challenging problem.
Domain Generalization via Inference-time Label-Preserving Target Projections
Generalization of machine learning models trained on a set of source domains on unseen target domains with different statistics, is a challenging problem.
FROCC: Fast Random projection-based One-Class Classification
We present Fast Random projection-based One-Class Classification (FROCC), an extremely efficient method for one-class classification.
Discrepancy Minimization in Domain Generalization with Generative Nearest Neighbors
Features extracted from this source domain are learned using a generative model whose latent space is used as a sampler to retrieve the nearest neighbors for the target data points.
