Kiran Sanjeevan Cabeza
pytorch Spectrogram + CNN + LSTM networks for audio classification on the UrbanSound8K dataset
contributions to pytorch/audio
acknowledgement in the torchaudio paper; implementations such as phase vocoder on GPU, or spectrogram time and frequency masking:
keras / tensorflow implementation of the state-of-the-art object detection system You only look once
a toy library and tutorial for learning the idea behind autodiff
contribution to mlflow
changes to allow mlflow docker projects to use GPU:
learned image compression based on CNNs in tensorflow
numerically compute the receptive field of a conv block in pytorch
density estimation using random forests and KDE
implementation of Mapper (Topological Data Analysis technique) for extracting insights from high dimensional data
simple pytorch model parser from a .cfg file
