Constructing Extreme Learning Machines with zero Spectral Bias

no code implementations • 19 Jul 2023 • Kaumudi Joshi, Vukka Snigdha, Arya Kumar Bhattacharya

The phenomena of Spectral Bias, where the higher frequency components of a function being learnt in a feedforward Artificial Neural Network (ANN) are seen to converge more slowly than the lower frequencies, is observed ubiquitously across ANNs.

Investigations on convergence behaviour of Physics Informed Neural Networks across spectral ranges and derivative orders

no code implementations • 7 Jan 2023 • Mayank Deshpande, Siddharth Agarwal, Vukka Snigdha, Arya Kumar Bhattacharya

An important inference from Neural Tangent Kernel (NTK) theory is the existence of spectral bias (SB), that is, low frequency components of the target function of a fully connected Artificial Neural Network (ANN) being learnt significantly faster than the higher frequencies during training.

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