4 accepted papers
The modeling of genomic sequences presents unique challenges due to their long length and structural complexity. Traditional sequence models struggle to capture long-range dependencies and biological features inherent in DNA. In this work, we propose TrinityDNA, a novel DNA foundational model design
Distance based knowledge graph embedding methods show promising results on link prediction task, on which two topics have been widely studied: one is the ability to handle complex relations, such as N-to-1, 1-to-N and N-to-N, the other is to encode various relation patterns, such as symmetry/antisym…
Connectionist Temporal Classification (CTC) is a training criterion designed for sequence labelling problems where the alignment between the inputs and the target labels is unknown. One of the key steps is to add a blank symbol to the target vocabulary. However, CTC tends to output spiky distributio…
Human emotion is a temporally dynamic event which can be inferred from both audio and video feature sequences. In this paper we investigate the long short term memory recurrent neural network (LSTM-RNN) based encoding method for category emotion recognition in the video. LSTM-RNN is able to incorpor…