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2020 – today
- 2024
[j3]Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado:
Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization. J. Cheminformatics 16(1): 115 (2024)- 2023
- [c1]Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato:
Tanimoto Random Features for Scalable Molecular Machine Learning. NeurIPS 2023 - [i4]Austin Tripp
, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato:
Tanimoto Random Features for Scalable Molecular Machine Learning. CoRR abs/2306.14809 (2023) - 2022
- [j2]Miguel García-Ortegón, Gregor N. C. Simm, Austin J. Tripp, José Miguel Hernández-Lobato, Andreas Bender, Sergio Bacallado:
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design. J. Chem. Inf. Model. 62(15): 3486-3502 (2022) - [i3]Miguel Garcia-Ortegon, Andreas Bender, Sergio Bacallado:
Conditional Neural Processes for Molecules. CoRR abs/2210.09211 (2022) - 2021
- [i2]Miguel García-Ortegón, Gregor N. C. Simm, Austin J. Tripp, José Miguel Hernández-Lobato, Andreas Bender, Sergio Bacallado:
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design. CoRR abs/2110.15486 (2021)
2010 – 2019
- 2017
- [i1]Annie Marsden, Sergio Bacallado:
Sequential Matrix Completion. CoRR abs/1710.08045 (2017) - 2015
- [j1]Sergio Bacallado, Persi Diaconis, Susan P. Holmes:
de Finetti Priors using Markov chain Monte Carlo computations. Stat. Comput. 25(4): 797-808 (2015)
Coauthor Index
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