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Found 8 papers, 5 papers with code
Spatio-temporal neural structural causal models for bike flow prediction
In addition, due to the disturbance of incomplete observations in the data, random contextual conditions lead to spurious correlations between data and features, making the prediction of the model ineffective in special scenarios.
Causal conditional hidden Markov model for multimodal traffic prediction
Recent works overemphasize spatio-temporal correlations of traffic flow, ignoring the physical concepts that lead to the generation of observations and their causal relationship.
Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design
Structure-based drug design is drawing growing attentions in computer-aided drug discovery.
Channel Self-Supervision for Online Knowledge Distillation
Recently, researchers have shown an increased interest in the online knowledge distillation.
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model
The key problem in the protein sequence representation learning is to capture the co-evolutionary information reflected by the inter-residue co-variation in the sequences.
Assessing Attendance by Peer Information
Attendance rate is an important indicator of students' study motivation, behavior and Psychological status; However, the heterogeneous nature of student attendance rates due to the course registration difference or the online/offline difference in a blended learning environment makes it challenging to compare attendance rates.
An ensemble CNN method for biomedical entity normalization
Different representations of the same concept could often be seen in scientific reports and publications.
Ranked #2 on
Medical Concept Normalization
on BB-norm-phenotype
