1 code implementation • 23 Nov 2021 • Stanley Bryan Z. Hua, Alex X. Lu, Alan M. Moses
Motivation: In recent years, image-based biological assays have steadily become high-throughput, sparking a need for fast automated methods to extract biologically-meaningful information from hundreds of thousands of images.
Ranked #1 on BBBC021 NSC Accuracy on CytoImageNet
no code implementations • 25 Apr 2021 • Tianyu Lu, Alex X. Lu, Alan M. Moses
Large self-supervised models pretrained on millions of protein sequences have recently gained popularity in generating embeddings of protein sequences for protein function prediction.
1 code implementation • 14 May 2020 • Rohit Saha, Abenezer Teklemariam, Ian Hsu, Alan M. Moses
We propose a fully convolutional autoencoder network that takes as input two images and generates upto seven intermediate images.
1 code implementation • NeurIPS 2019 • Alex X. Lu, Amy X. Lu, Wiebke Schormann, Marzyeh Ghassemi, David W. Andrews, Alan M. Moses
Understanding if classifiers generalize to out-of-sample datasets is a central problem in machine learning.
no code implementations • 22 Dec 2010 • Amin Zia, Alan M. Moses
Here, however, we derive the theoretical dependence of false positives on dataset size and find that false positives can arise as a result of large dataset size, irrespective of the algorithm used.