Beyond the training set: an intuitive method for detecting distribution shift in model-based optimization

no code implementations • 9 Nov 2023 • Farhan Damani, David H Brookes, Theodore Sternlieb, Cameron Webster, Stephen Malina, Rishi Jajoo, Kathy Lin, Sam Sinai

A common scenario involves using a fixed training set to train models, with the goal of designing new samples that outperform those present in the training data.

Black Box Recursive Translations for Molecular Optimization

no code implementations • 21 Dec 2019 • Farhan Damani, Vishnu Sresht, Stephen Ra

We call this method Black Box Recursive Translation (BBRT), a new inference method for molecular property optimization.

Drug Discovery Molecular Graph Generation +1

Discrete Object Generation with Reversible Inductive Construction

1 code implementation • NeurIPS 2019 • Ari Seff, Wenda Zhou, Farhan Damani, Abigail Doyle, Ryan P. Adams

The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs.

Denoising Object +1