5 citations · 10 across the 4 of their papers we have counts for
4 papers
Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction
Karina Zadorozhny, Kangway V. Chuang, Bharath Sathappan +3
Accurate prediction of molecular activities is crucial for efficient drug discovery, yet remains challenging due to limited and noisy datasets. We introduce Similarity-Quantized Re…
Protein Discovery with Discrete Walk-Jump Sampling
Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny +10
We resolve difficulties in training and sampling from a discrete generative model by learning a smoothed energy function, sampling from the smoothed data manifold with Langevin Mar…
Deep Denerative Models for Drug Design and Response
Karina Zadorozhny, Lada Nuzhna
Designing new chemical compounds with desired pharmaceutical properties is a challenging task and takes years of development and testing. Still, a majority of new drugs fail to pro…
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation
Karina Zadorozhny, Patrick Thoral, Paul Elbers +1
Detection of Out-of-Distribution (OOD) samples in real time is a crucial safety check for deployment of machine learning models in the medical field. Despite a growing number of un…