16 citations · 37 across the 19 of their papers we have counts for
3 papers · 1 filter
In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review
Amelia Jiménez-Sánchez, Natalia-Rozalia Avlona, Sarah de Boer +26
Datasets play a critical role in medical imaging research, yet issues such as label quality, shortcuts, and metadata are often overlooked. This lack of attention may harm the gener…
Disentanglement with Factor Quantized Variational Autoencoders
Gulcin Baykal, Melih Kandemir, Gozde Unal
Disentangled representation learning aims to represent the underlying generative factors of a dataset in a latent representation independently of one another. In our work, we propo…
EdVAE: Mitigating Codebook Collapse with Evidential Discrete Variational Autoencoders
Gulcin Baykal, Melih Kandemir, Gozde Unal
Codebook collapse is a common problem in training deep generative models with discrete representation spaces like Vector Quantized Variational Autoencoders (VQ-VAEs). We observe th…