23 citations · 33 across the 6 of their papers we have counts for
6 papers
On the distribution of cosine similarity with application to biology
Ian Smith, Janosch Ortmann, Farnoosh Abbas-Aghababazadeh +2
Cosine similarity is an established similarity metric for computing associations on vectors, and it is commonly used to identify related samples from biological perturbational data…
FastCPH: Efficient Survival Analysis for Neural Networks
Xuelin Yang, Louis Abraham, Sejin Kim +4
The Cox proportional hazards model is a canonical method in survival analysis for prediction of the life expectancy of a patient given clinical or genetic covariates -- it is a lin…
Evaluation of statistical approaches for association testing in noisy drug screening data
Petr Smirnov, Ian Smith, Zhaleh Safikhani +9
dentifying associations among biological variables is a major challenge in modern quantitative biological research, particularly given the systemic and statistical noise endemic to…
Reducing Adversarial Example Transferability Using Gradient Regularization
George Adam, Petr Smirnov, Benjamin Haibe-Kains +1
Deep learning algorithms have increasingly been shown to lack robustness to simple adversarial examples (AdvX). An equally troubling observation is that these adversarial examples…
Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples
George A. Adam, Petr Smirnov, David Duvenaud +2
Many deep learning algorithms can be easily fooled with simple adversarial examples. To address the limitations of existing defenses, we devised a probabilistic framework that can…
Dr.VAE: Drug Response Variational Autoencoder
Ladislav Rampasek, Daniel Hidru, Petr Smirnov +2
We present two deep generative models based on Variational Autoencoders to improve the accuracy of drug response prediction. Our models, Perturbation Variational Autoencoder and it…