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Kiran Sanjeevan Cabeza

crnn-audio-classification

pytorch Spectrogram + CNN + LSTM networks for audio classification on the UrbanSound8K dataset

acknowledgement in the torchaudio paper; implementations such as phase vocoder on GPU, or spectrogram time and frequency masking:

dourflow

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

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

randomforest-density-python

density estimation using random forests and KDE

mapper-tda

implementation of Mapper (Topological Data Analysis technique) for extracting insights from high dimensional data

simple pytorch model parser from a .cfg file