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Found 5 papers, 1 papers with code
Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models
The complex relationship between the setup structure of a quantum experiment and its entanglement properties is essential to fundamental research in quantum optics but is difficult to intuitively understand.
QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction
We study the problem of query attribute value extraction, which aims to identify named entities from user queries as diverse surface form attribute values and afterward transform them into formally canonical forms.
Graph-based Multilingual Product Retrieval in E-commerce Search
Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios.
Neural Message Passing on High Order Paths
Graph neural network have achieved impressive results in predicting molecular properties, but they do not directly account for local and hidden structures in the graph such as functional groups and molecular geometry.
Graph Deconvolutional Generation
Graph generation is an extremely important task, as graphs are found throughout different areas of science and engineering.
