9 citations · 16 across the 3 of their papers we have counts for
3 papers
Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions
Lucian Chan, Marcel Verdonk, Carl Poelking
Predicting the bioactivity of a ligand is one of the hardest and most important challenges in computer-aided drug discovery. Despite years of data collection and curation efforts b…
3D pride without 2D prejudice: Bias-controlled multi-level generative models for structure-based ligand design
Lucian Chan, Rajendra Kumar, Marcel Verdonk +1
Generative models for structure-based molecular design hold significant promise for drug discovery, with the potential to speed up the hit-to-lead development cycle, while improvin…
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings
Jean-Francois Ton, Lucian Chan, Yee Whye Teh +1
Current meta-learning approaches focus on learning functional representations of relationships between variables, i.e. on estimating conditional expectations in regression. In many…