Search Results for author: Nicholas Choma

Found 5 papers, 3 papers with code

Benchmarking GPU and TPU Performance with Graph Neural Networks

no code implementations21 Oct 2022 Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura

Many artificial intelligence (AI) devices have been developed to accelerate the training and inference of neural networks models.


Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

4 code implementations ICLR 2022 Yulun Wu, Mikaela Cashman, Nicholas Choma, Érica T. Prates, Verónica G. Melesse Vergara, Manesh Shah, Andrew Chen, Austin Clyde, Thomas S. Brettin, Wibe A. de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain.

Drug Discovery Graph Attention

Graph Neural Networks for IceCube Signal Classification

1 code implementation17 Sep 2018 Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna

Tasks involving the analysis of geometric (graph- and manifold-structured) data have recently gained prominence in the machine learning community, giving birth to a rapidly developing field of geometric deep learning.

Classification General Classification

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