: NLP Vocabulary: siamese neural network

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siamese neural network

A pair of neural networks that share their weights and aims at computing similarity functions. (ScienceDirect)

A siamese neural network consists of twin networks which accept distinct inputs but are joined by an energy function at the top. (Goyal, 2017)

Each encoder network in the twin network is a 5-layer MLP with a 20% dropout between the layers and an output embedding vector of dimension 384. (Kumaran, Rowe, Mott, Chaturvedi & Lester, 2023)
Serdyuk et al. (2017) proposed a twin network to regularize the hidden states of the left-to-right decoder with the future-aware right-toleft decoder. (Liu, Tan, Tao, Fu, Zhao, Liu & Yan, 2022)
Since BERT provides a deep bidirectional representation conditioned on text in both directions we expect this method to perform better than the twin neural network which uses GLOVE embeddings. (Daryani & Caverlee, 2021)
The canonical Siamese neural network is an architecture that consists of two towers with shared weights working in parallel on two different inputs. (Yuan, Merler, Choudhury, Pavuluri, Singh & Vukovic, 2023)
This study leverages various machine learning (ML) approaches including Support Vector Regression (SVR) and Random Forest deep learning (DL) techniques such as Siamese Neural Networks and transformerbased models such as MiniLM-L6-v2 Marathisbert Telugu-sentence-bert-nli and Robertabne-sentiment-analysis-es to assess semantic relatedness across English Marathi Telugu and Spanish. (Hossain, Paran, Shohan, Hossain & Hoque, 2024)

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