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Found 6 papers, 4 papers with code
WISER: Weak supervISion and supErvised Representation learning to improve drug response prediction in cancer
Cancer, a leading cause of death globally, occurs due to genomic changes and manifests heterogeneously across patients.
Fusing Conditional Submodular GAN and Programmatic Weak Supervision
In our work, we address these challenges by (i) implementing a noise-aware classifier using the pseudo labels generated by the label model (ii) utilizing the noise-aware classifier's prediction to train the label model and generate class-conditional images.
Bayesian Pseudo-Coresets via Contrastive Divergence
This approximation is achieved by optimizing a divergence measure between the true posterior and the pseudo-coreset posterior.
One-shot domain adaptation for semantic face editing of real world images using StyleALAE
Results show that our approach can generate semantic modifications on any real world facial image while preserving the identity.
Weakly-Supervised Classification and Detection of Bird Sounds in the Wild.
It is easier to hear birds than see them, however, they still play an essential role in nature and they are excellent indicators of deteriorating environmental quality and pollution.
Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation
In our work, we have formulated a Markov Decision Process (MDP) over the latent space of a pre-trained GAN model to learn a conditional policy for semantic manipulation along specific attributes under defined identity bounds.
