#rust #audio_processing #digital_signal_processing #dsp #fft #fourier_transform

https://github.com/calebzulawski/fourier

#python #text_classification #text #transformer #vision #image_classification #feedforward_neural_network #language_model #fourier_transform #fnet

https://github.com/rishikksh20/FNet-pytorch

#jupyter_notebook #cnn #colab #colab_notebook #computer_vision #deep_learning #deep_neural_networks #fourier #fourier_convolutions #fourier_transform #gan #generative_adversarial_network #generative_adversarial_networks #high_resolution #image_inpainting #inpainting #inpainting_algorithm #inpainting_methods #pytorch

https://github.com/saic-mdal/lama

#python #fno #fourier_neural_operator #neural_operator #neural_operators #partial_differential_equations #pde #pytorch #tensor_methods #tensorization #tensorly #uno

The `neuraloperator` library is a powerful tool for learning neural operators in PyTorch. It allows you to learn mappings between function spaces, which is different from regular neural networks. This library is useful because it makes your trained models work with data of any resolution, meaning you don't have to worry about the size of your data. You can easily install it using `pip install neuraloperator` and start training operators right away. The library also offers efficient models like the Tucker Tensorized FNO, which reduces the number of parameters needed, making it faster and more efficient. This helps you train and use complex models more effectively.

https://github.com/neuraloperator/neuraloperator

#jupyter_notebook #cnn #colab #colab_notebook #computer_vision #deep_learning #deep_neural_networks #fourier #fourier_convolutions #fourier_transform #gan #generative_adversarial_network #generative_adversarial_networks #high_resolution #image_inpainting #inpainting #inpainting_algorithm #inpainting_methods #pytorch

LaMa is a powerful tool for removing objects from images. It uses special techniques called Fourier Convolutions, which help it understand the whole image at once. This makes it very good at filling in large areas that are missing. LaMa can even work well with high-resolution images, even if it was trained on smaller ones. This means you can use it to fix photos where objects are in the way, making them look natural and complete again.

https://github.com/advimman/lama