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Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding
While end-to-end learning systems are rapidly gaining capabilities and popularity, the increasing computational demands for deploying such systems, along with a lack of flexibility, adaptability, explainability, reasoning and verification capabilities, require new types of architectures.
Mean Shift Rejection: Training Deep Neural Networks Without Minibatch Statistics or Normalization
This new technique allows direct training of the test graph so that training and test models are identical.
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