We evaluate several neural-network architectures. both convolutional and recurrent. for gravitational-wave time-series feature extraction by performing point parameter estimation on noisy waveforms from binary-black-hole mergers. We build datasets of 100 000 elements for each of four different waveform models (or approximants) in order to test how approximant choice affects feature ex... https://fitnessgravesyardes.shop/product-category/clevis-axle/