China’s DeepSeek has made innovations in the cost of AI and innovations like mixture of experts (MoE) and fine-grain expert ...

Thus, we propose a stratigraphic-encoded Transformer algorithm, named SeisWellTrans, to build a gamma log inversion model using horizon position encoding and seismic trace as inputs. Specifically, the ...

🔹 Why Do We Need Positional Encoding? Transformers do not process words sequentially like RNNs or LSTMs. Instead, they analyze all words at once using self-attention. But this creates a problem: 👉 ...

Specifically, TRTST explores combining a text transformer encoder with an image transformer ... We also propose a new adaptive parametric positional encoding (APPE) scheme which can adaptively produce ...

Both type of positional encoding better then not using any type of positional ... GPT was trained on this and original Transformer too. Used more commonly. Relative: Suitable for language modelling ...