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Found 6 papers, 4 papers with code
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge
Accurate prediction of protein-ligand binding structures, a task known as molecular docking is crucial for drug design but remains challenging.
Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
We then propose an Architecture-Agnostic Masked Image Modeling framework (A$^2$MIM), which is compatible with both Transformers and CNNs in a unified way.
An Empirical Study: Extensive Deep Temporal Point Process
In this paper, we first review recent research emphasis and difficulties in modeling asynchronous event sequences with deep temporal point process, which can be concluded into four fields: encoding of history sequence, formulation of conditional intensity function, relational discovery of events and learning approaches for optimization.
GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
Recent years have witnessed great success in handling node classification tasks with Graph Neural Networks (GNNs).
Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive
In this survey, we extend the concept of SSL, which first emerged in the fields of computer vision and natural language processing, to present a timely and comprehensive review of existing SSL techniques for graph data.
Conditional Local Convolution for Spatio-temporal Meteorological Forecasting
We further propose the distance and orientation scaling terms to reduce the impacts of irregular spatial distribution.
