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Over 200 Ukrainian military experts in Gulf region to counter Iran's drones
Over 200 Ukrainian military experts in Gulf region to counter Iran's drones More than 200 Ukrainian military experts are in the Gulf region and wider Middle East helping governments in their defence against Iran's drone attacks, Ukraine's President Volodymyr Zelenskyy has said. In an address to dozens of members of the United Kingdom Parliament in London on Tuesday, the Ukrainian leader said 201 Ukrainian anti-drone experts are in the region and another 34 "are ready to deploy". "Our teams are already in the Emirates, Qatar, Saudi Arabia, and on the way to Kuwait," the Ukrainian leader said. "We are working with several other countries - agreements are already in place. We do not want this terror of the Iranian regime against its neighbours to succeed," he said.
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Learning Latent Subspaces in Variational Autoencoders
Variational autoencoders (VAEs) are widely used deep generative models capable of learning unsupervised latent representations of data. Such representations are often difficult to interpret or control. We consider the problem of unsupervised learning of features correlated to specific labels in a dataset. We propose a VAE-based generative model which we show is capable of extracting features correlated to binary labels in the data and structuring it in a latent subspace which is easy to interpret. Our model, the Conditional Subspace VAE (CSVAE), uses mutual information minimization to learn a low-dimensional latent subspace associated with each label that can easily be inspected and independently manipulated. We demonstrate the utility of the learned representations for attribute manipulation tasks on both the Toronto Face and CelebA datasets.
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