BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks
Hakhamaneshi et al.: https://arxiv.org/abs/1907.10515
#SignalProcessing #MachineLearning #NeuralComputing
Hakhamaneshi et al.: https://arxiv.org/abs/1907.10515
#SignalProcessing #MachineLearning #NeuralComputing
DDSP: Differentiable Digital Signal Processing
Engel et al.
⌨️ Blog: http://magenta.tensorflow.org/ddsp
🎵 Examples: https://g.co/magenta/ddsp-examples
⏯ Colab: http://g.co/magenta/ddsp-demo
💻 Code: http://github.com/magenta/ddsp
📝 Paper: http://g.co/magenta/ddsp-paper
#ArtificialIntelligence #TensorFlow #SignalProcessing
Engel et al.
⌨️ Blog: http://magenta.tensorflow.org/ddsp
🎵 Examples: https://g.co/magenta/ddsp-examples
⏯ Colab: http://g.co/magenta/ddsp-demo
💻 Code: http://github.com/magenta/ddsp
📝 Paper: http://g.co/magenta/ddsp-paper
#ArtificialIntelligence #TensorFlow #SignalProcessing
Magenta
DDSP: Differentiable Digital Signal Processing
Today, we’re pleased to introduce the Differentiable Digital Signal Processing (DDSP) library. DDSP lets you combine the interpretable structure of classical...