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Found 6 papers, 1 papers with code
Variational Laplace Autoencoders
Based on the Laplace approximation of the latent variable posterior, VLAEs enhance the expressiveness of the posterior while reducing the amortization error.
Continual Learning on Noisy Data Streams via Self-Purified Replay
Continually learning in the real world must overcome many challenges, among which noisy labels are a common and inevitable issue.
Imbalanced Continual Learning with Partitioning Reservoir Sampling
Continual learning from a sequential stream of data is a crucial challenge for machine learning research.
AudioCaps: Generating Captions for Audios in The Wild
We explore the problem of Audio Captioning: generating natural language description for any kind of audio in the wild, which has been surprisingly unexplored in previous research.
Ranked #9 on
Audio captioning
on AudioCaps
Generative Adversarial Parallelization
Generative Adversarial Networks have become one of the most studied frameworks for unsupervised learning due to their intuitive formulation.
Generating images with recurrent adversarial networks
Gatys et al. (2015) showed that optimizing pixels to match features in a convolutional network with respect reference image features is a way to render images of high visual quality.
