Jeff Waller

Collecting Links LMVP: Vido predictor with Leaked Motion Information Geometry-Based Bext Frame Prediction from Monocular Video Predicting Future Frames using Retrospective Cycle GAN Next-frame prediction with Conv-LSTM

Collecting links Variational autoencoder implementation in keras with a custom training step Custom Training Using the Strategy Class. Withing a custom loss function, it's sometimes necessary to get the epoch number. Some reserch in determining, controlling the VAE loss function to avoid posterior collapse in Re-balancing Variational Autoencoder Loss for

Overcoming error: no video mode activated A bug certainly. There are at least 2 reasons. It's connected to the use of GRUB_TIMEOUT_STYLE part of the fix is to unset this as described here #GRUB_TIMEOUT_STYLE=hidden GRUB_TIMEOUT_STYLE=menu GRUB_TIMEOUT=10 Additionally, there is a

There are at least 5 dependencies here. Software dependency on TensorFlow version. TensorFlow dependency on python version. TensorFlow dependency on cuda and cuDNN Cuda dependency on NVidia drivers. NVidia driver dependency on NVidia hardware. Software Dependency Starting with an (opensource) software install, the typical method calls for installation of various

Construction an autoencoder (A) is a unsupervised learning NN technique in which an input X is mapped to itself X->A->X. Importantly there are multiple layers in this NN which contains in the interior a "bottleneck" which has a capacity smaller than the input and