Machine Learning Custom Architectures (Pytorch)

I am developing a neural network for machine learning and artificial general intelligence and am having more difficulty than I would like with pytorch. The final architecture will be a bit different than what is currently available and requires custom layers, loss functions and optimizers. I need the code to be easy for a novice programmer to follow and the final code can be in pytorch and should use the gpu.

Please be familiar with all aspects of machine learning including computer vision, NLP, segmentation, etc.

I may use existing architectures e.g. clustering algorithms (Annoy, K-means), sequential networks (transformers, LSTMs), convnets, etc so need someone who is comfortable incorporating existing libraries into the custom framework.

I have a very specific architecture in mind for preliminary testing but may have more work down the road for development of an AGI.

This is going to be a fun and interesting job. If the architecture works well, the hope is to publish and you would be included as a co-author.

Please let me know what custom architecture experience in pytorch you've had and how much time per week you can dedicate.

Thank you

Skills: Machine Learning (ML), CUDA, Algorithm, Java, Python

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Project ID: #24596574

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