We propose Denoising Masked Autoencoder (Deno-MAE), a novel multimodal autoencoder framework for denoising modulation signals during pretraining. DenoMAE extends the concept of masked autoencoders by ...

It integrates a transmission spectrum autoencoder and a photonic energy band autoencoder, processing energy band data to predict the corresponding transmission spectrum. The results indicate that ...

GPT-4.5 has successfully convinced people it’s human 73% of the time in an authentic configuration of the original Turing test.

The trained neural autoencoder model is used to reduce the 200 data items. ... The 9-2-9 autoencoder in the diagram has (9 * 2) + (2 * 9) = 36 weights, and 2 + 9 = 11 biases. The values of the weights ...

At this point, in a non-demo scenario, the anomalous data item would be examined further to try and determine why the autoencoder model flagged the item as anomalous. ... The 9-2-9 autoencoder in the ...

The structure of the feature autoencoder is shown in Figure 2A; it takes the gene expression matrix, composed of the first 2000 genes obtained after removing the low-expression cells and genes, and ...

2. CAE training: A schematic diagram is shown. 3D images of the Kyoto dataset were input, feature was extracted, and the original image was reproduced. 3. Feature extraction: the model trained using ...