Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials. Retrieved May 24, 2026, from https://4ort.xyz/entity/crysgnn-distilling-pre-trained-knowledge-to-enhance-property-prediction-for-crystalline-materials
MLA“CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/crysgnn-distilling-pre-trained-knowledge-to-enhance-property-prediction-for-crystalline-materials.
BibTeX@misc{4ortxyz_crysgnn-distilling-pre-trained-knowledge-to-enhance-property-prediction-for-crystalline-materials_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials}}, year = {2026}, url = {https://4ort.xyz/entity/crysgnn-distilling-pre-trained-knowledge-to-enhance-property-prediction-for-crystalline-materials}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): CrysGNN: Distilling Pre-trained Knowledge to Enhance Property Prediction for Crystalline Materials — https://4ort.xyz/entity/crysgnn-distilling-pre-trained-knowledge-to-enhance-property-prediction-for-crystalline-materials (retrieved 2026-05-24)