Implementing Robust and Efficient Pseudo-transient Methods for Solving Neural Complementarity Problems in Julia
Traditional deep learning models typically consist of explicitly defined layers, such as fully connected and self-attention layers found in Transformers, which have been pivotal in recent advancements in computer vision and large language models. Selecting an appropriate architecture is critical for...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/153881 |