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Found 4 papers, 1 papers with code
Knowledge Graph Question Answering for Materials Science (KGQA4MAT): Developing Natural Language Interface for Metal-Organic Frameworks Knowledge Graph (MOF-KG) Using LLM
To evaluate the benchmark, we have developed a systematic approach for utilizing the LLM, ChatGPT, to translate natural language questions into formal KG queries.
CompNet: A Designated Model to Handle Combinations of Images and Designed features
This is a specially designed neural network that accepts combinations of images and designed features as input in order to leverage all available information.
Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies
Metal-Organic Frameworks (MOFs) are a class of modular, porous crystalline materials that have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, catalysis, and drug delivery.
Visual Explanations from Deep Networks via Riemann-Stieltjes Integrated Gradient-based Localization
One such technique is the Gradient-based Class Activation Map (Grad-CAM), which is able to locate features of an input image at various levels of a convolutional neural network (CNN), but is sensitive to the vanishing gradients problem.
