Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

We analyze kinematics and dynamics solvers as the main representatives of algorithms that perform computations ... or even simply localized graph traversals. We have implemented the synthesizer using ...

However, when dealing with large graphs, most of the existing libraries still have two limitations. The first one is inadequate consideration of scaling strategies. Most libraries only implement ...

It enables users to write pure Python code to project graphs, run algorithms, as well as define and use machine learning pipelines in GDS. The API is designed to mimic the GDS Cypher procedure API in ...

Using real-life and synthetic graphs, we experimentally verify that partition-transparent algorithms compute correct answers under different partitions; better still, under hybrid partitions these ...

Knowledge Graph is an ER-based (Entity-Relationship ... This library incorporates Bayesian Optimizer to perform the hyper-parameters discovery. Pykg2vec is built using Python on top of the PyTorch ...