Much of the discussion in the previous chapters has focused on a bag-of-words representation of text. While the bag-of-words representation is sufficient in many practical applications, there are cases in which the sequential aspects of text become more important.CharuC.Aggarwal
Here, we present a deep learning model (DLM) for predicting Next-Generation Sequencing (NGS) depth from DNA probe sequences. Our DLM includes a bidirectional recurrent neural network that takes as input both DNA nucleotide identities as well as the calculated probability of the nucleotide being ...
1997). Another review of the field is provided a decade ago inLipton et al. (2015). A general survey of deep learning models is presented inSamira et al. (2018). Details of an RNN on how the vectors are segregated into batches and processed are provided inKalidas (2020). ...
This series of blog posts aims to provide an intuitive and gentle introduction todeep learningthat does not rely heavily on math or theoretical constructs.The first partof this series provided an overview of the field of deep learning, covering fundamental and core concepts.The second partof the ...
The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shape in
Deep learning practitioners commonly regard recurrent architectures as the default starting point for sequence modeling tasks. The sequence modeling chapter in the canonical textbook on deep learning is titled “Sequence Modeling: Recurrent and Recursive Nets” (Goodfellow et al., 2016), capturing the ...
This example shows how to predict the remaining useful life (RUL) of engines by using deep learning.
title={Decision transformer: Reinforcement learning via sequence modeling}, author={Chen, Lili and Lu, Kevin and Rajeswaran, Aravind and Lee, Kimin and Grover, Aditya and Laskin, Misha and Abbeel, Pieter and Srinivas, Aravind and Mordatch, Igor}, ...
Language modeling is one of the most basic and important tasks in natural language processing. There's also one that RNNs do very well. In this video, you learn about how to build a language model using an RNN, and this will lead up to a fun programming exercise at the end of this ...
“An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.” Preprint, submitted April 19, 2018. https://arxiv.org/abs/1803.01271. [2] Oord, Aaron van den, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andr...