Generative artificial intelligence models present a fresh approach to chemogenomics and de
novo drug design, as they provide researchers with the ability to narrow down their search of …

We propose a new STAckable Recurrent cell (STAR) for recurrent neural networks (RNNs),
which has fewer parameters than widely used LSTM [16] and GRU [10] while being more …

Although both convolutional and recurrent architectures have a long history in sequence
prediction, the current" default" mindset in much of the deep learning community is that …

Context With the wide application of deep learning in drug research and development, de
novo molecular design methods based on recurrent neural network (RNN) have strong …

We introduce Independently Recurrent Long Short-term Memory cells: IndyLSTMs. These
differ from regular LSTM cells in that the recurrent weights are not modeled as a full matrix …

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious
threat to public health and prompted researchers to find anti-coronavirus 2019 (COVID-19) …

In this work, we present the Grounded Recurrent Neural Network (GRNN), a recurrent neural
network architecture for multi-label prediction which explicitly ties labels to specific …

Recurrent neural networks (RNNs) are omnipresent in sequence modeling tasks. Practical
models usually consist of several layers of hundreds or thousands of neurons which are fully …

With recent advances in artificial intelligence, recurrent neural networks have successfully
generated pleasing melodies; however, they have struggled to create a full song that has …

Music language models play an important role for various music signal and symbolic music
processing tasks, such as music generation, symbolic music classification, or automatic …