activity
20202022
most citedProtein Folding Neural Networks Are Not Robust

12 citations · 13 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG2022

A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks

Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez

The success of machine learning solutions for reasoning about discrete structures has brought attention to its adoption within combinatorial optimization algorithms. Such approache…

q-bio.BM202112 cited

Protein Folding Neural Networks Are Not Robust

Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz +2

Deep neural networks such as AlphaFold and RoseTTAFold predict remarkably accurate structures of proteins compared to other algorithmic approaches. It is known that biologically sm…

cs.CV2021

Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks

Edward Verenich, Tobias Martin, Alvaro Velasquez +2

Convolutional neural networks (CNN) are now being widely used for classifying and detecting pulmonary abnormalities in chest radiographs. Two complementary generalization propertie…

cs.LG20201 cited

An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks

Sumit Kumar Jha, Susmit Jha, Rickard Ewetz +4

Deep neural networks have been shown to be vulnerable to membership inference attacks wherein the attacker aims to detect whether specific input data were used to train the model.…

cs.CV2020

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia

Edward Verenich, Alvaro Velasquez, Nazar Khan +1

Trust in predictions made by machine learning models is increased if the model generalizes well on previously unseen samples and when inference is accompanied by cogent explanation…

cs.NE2020

Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture

Alvaro Velasquez, Christopher H. Bennett, Naimul Hassan +5

We propose a hardware learning rule for unsupervised clustering within a novel spintronic computing architecture. The proposed approach leverages the three-terminal structure of do…