@thisismadani Do you have any comparisons to the simpler strategy of conditioning the decoder directly on the desired properties? https://t.co/KWQQHQXFMB https://t.co/UwTqqYpfAB
RT @shion_honda: Molecular generative model based on CVAE [Lim+, 2018, J. Cheminform.] 3層LSTMベースのCVAEをZINCのSMILESで訓練した。分子量やLogPなど5つの性質で条件付け…
RT @shion_honda: Molecular generative model based on CVAE [Lim+, 2018, J. Cheminform.] 3層LSTMベースのCVAEをZINCのSMILESで訓練した。分子量やLogPなど5つの性質で条件付け…
Molecular generative model based on CVAE [Lim+, 2018, J. Cheminform.] 3層LSTMベースのCVAEをZINCのSMILESで訓練した。分子量やLogPなど5つの性質で条件付けた分子の生成が可能。1つの性質に関して訓練データの範囲を超えて生成することもできた。 https://t.co/FBL8csPk6v #NowReading https://t.co/vGSwldK4KJ
RT @jcheminf: new: "Molecular generative model based on conditional variational autoencoder for de novo molecular design" https://t.co/ca3r…
RT @jcheminf: new: "Molecular generative model based on conditional variational autoencoder for de novo molecular design" https://t.co/ca3r…
new: "Molecular generative model based on conditional variational autoencoder for de novo molecular design" https://t.co/ca3rlWVKm6 https://t.co/7JNyUVuhF6
Molecular generative model based on conditional variational autoencoder for de novo molecular design https://t.co/3YViuKpgwM #bioinformatics
Molecular generative model based on conditional variational autoencoder for de novo molecular design https://t.co/Gz3ZbFa3ca #bioinformatics