未登录MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary InformationMELLODDY: 跨制药联合学习以前所未有的规模在不损害专有信息的情况下解锁QSAR的好处
Heyndrickx, Wouter; Mervin, Lewis; Morawietz, Tobias; Sturm, Noe; Friedrich, Lukas; Zalewski, Adam; Pentina, Anastasia; Humbeck, Lina; Oldenhof, Martijn; Niwayama, Ritsuya; Schmidtke, Peter; Fechner, Nikolas; Simm, Jaak; Arany, Adam; Drizard, Nicolas; Jabal, Rama; Afanasyeva, Arina; Loeb, Regis; Verma, Shlok; Harnqvist, Simon; Holmes, Matthew; Pejo, Balazs; Telenczuk, Maria; Holway, Nicholas; Dieckmann, Arne; Rieke, Nicola; Zumsande, Friederike; Clevert, Djork-Arne; Krug, Michael; Luscombe, Christopher; Green, Darren; Ertl, Peter; Antal, Peter; Marcus, David; Do Huu, Nicolas; Fuji, Hideyoshi; Pickett, Stephen; Acs, Gergely; Boniface, Eric; Beck, Bernd; Sun, Yax; Gohier, Arnaud; Rippmann, Friedrich; Engkvist, Ola; Goeller, Andreas H.; Moreau, Yves; Galtier, Mathieu N.; Schuffenhauer, Ansgar; Ceulemans, Hugo
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