no code implementations • 5 Mar 2024 • Aashaka Desai, Maartje De Meulder, Julie A. Hochgesang, Annemarie Kocab, Alex X. Lu
Growing research in sign language recognition, generation, and translation AI has been accompanied by calls for ethical development of such technologies.
1 code implementation • 30 Sep 2022 • Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini
The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases.
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 • CVPR 2021 • Karren Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi Jaakkola, Caroline Uhler
In this paper, we aim to synthesize cell microscopy images under different molecular interventions, motivated by practical applications to drug development.
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.
no code implementations • 25 Dec 2020 • Amy X. Lu, Alex X. Lu, Alan Moses
Self-supervised representation learning of biological sequence embeddings alleviates computational resource constraints on downstream tasks while circumventing expensive experimental label acquisition.
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.