Meet ResFields: A Novel AI Approach to Overcome the Limitations of Spatiotemporal Neural Fields in Effectively Modeling Long and Complex Temporal Signals

The most popular neural network architecture for representing neural continuous spatiotemporal fields, also known as neural fields, is the multi-layer perceptron. This is because it can encode continuous signals over arbitrary dimensions, has built-in implicit regularisation, and has a spectral bias that facilitates effective interpolation. Thanks to these exceptional features, MLPs have achieved great success […]

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