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Paper Review

Paper Review #5 - Attention Is All You Need
Paper Review 2021. 7. 13. Paper Review #5 - Attention Is All You Need Attention Is All You Need (2017.12.06) - https://arxiv.org/abs/1706.03762 Attention Is All You Need The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new arxiv.org Research direction & Motivation ..
Paper Review #4 - Learning Phrase Representations using RNN Encoder-Decoder Statistical Machine Translation
Paper Review 2021. 7. 2. Paper Review #4 - Learning Phrase Representations using RNN Encoder-Decoder Statistical Machine Translation Learning Phrase Representations using RNN Encoder-Decoder Statistical Machine Translation (2014.06.03) - https://arxiv.org/abs/1406.1078 Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of s..
Paper Review #3 - On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Paper Review 2021. 6. 29. Paper Review #3 - On the Properties of Neural Machine Translation: Encoder-Decoder Approaches On the Properties of Neural Machine Translation: Encoder-Decoder Approaches (2014.10.07) - https://arxiv.org/abs/1409.1259 On the Properties of Neural Machine Translation: Encoder-Decoder Approaches Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a dec..
Paper Review #2 - Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Paper Review 2021. 6. 26. Paper Review #2 - Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling (2014.12.11) https://arxiv.org/abs/1412.3555 Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long sho..
Paper Review #1 - Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Paper Review 2021. 6. 26. Paper Review #1 - Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (2015.03.02) - https://arxiv.org/abs/1502.03167 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous lay..

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