{"total":12,"rows":[{"id":"2107.12375","title":"Geometric Deep Learning on Molecular Representations","created":"2021-07-26","cited_by_count":113,"area":null},{"id":"2106.03609","title":"High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning","created":"2021-06-07","cited_by_count":54,"area":null},{"id":"2305.09481","title":"Context-enriched molecule representations improve few-shot drug discovery","created":"2023-04-24","cited_by_count":24,"area":null},{"id":"2310.02902","title":"Searching for High-Value Molecules Using Reinforcement Learning and Transformers","created":"2023-10-04","cited_by_count":18,"area":null},{"id":"2303.00313","title":"Deep Learning Methods for Small Molecule Drug Discovery: A Survey","created":"2023-03-01","cited_by_count":10,"area":null},{"id":"2205.01592","title":"Conditional $\\beta$-VAE for De Novo Molecular Generation","created":"2022-05-01","cited_by_count":8,"area":null},{"id":"2310.02744","title":"SALSA: Semantically-Aware Latent Space Autoencoder","created":"2023-10-04","cited_by_count":4,"area":null},{"id":"2201.04929","title":"Improving VAE based molecular representations for compound property prediction","created":"2022-01-13","cited_by_count":3,"area":null},{"id":"2310.08685","title":"Kernel-Elastic Autoencoder for Molecular Design","created":"2023-10-12","cited_by_count":2,"area":null},{"id":"2106.13318","title":"Realistic molecule optimization on a learned graph manifold","created":"2021-06-03","cited_by_count":0,"area":null},{"id":"2406.06553","title":"Ensemble Model With Bert,Roberta and Xlnet For Molecular property prediction","created":"2024-05-30","cited_by_count":0,"area":null},{"id":"2408.03342","title":"Graph Residual based Method for Molecular Property Prediction","created":"2024-07-27","cited_by_count":0,"area":null}],"next_cursor":null}