Employing artificial intelligence to steer exascale workflows with colmena
Computational workflows are a common class of application on supercomputers, yet the
loosely coupled and heterogeneous nature of workflows often fails to take full advantage of …
loosely coupled and heterogeneous nature of workflows often fails to take full advantage of …
Multi-objective latent space optimization of generative molecular design models
Molecular design based on generative models, such as variational autoencoders (VAEs),
has become increasingly popular in recent years due to its efficiency for exploring high …
has become increasingly popular in recent years due to its efficiency for exploring high …
ChemoGraph: interactive visual exploration of the chemical space
Exploratory analysis of the chemical space is an important task in the field of
cheminformatics. For example, in drug discovery research, chemists investigate sets of …
cheminformatics. For example, in drug discovery research, chemists investigate sets of …
Ai-coupled hpc workflows
Increasingly, scientific discovery requires sophisticated and scalable workflows. Workflows
have become the``new applications,''wherein multi-scale computing campaigns comprise …
have become the``new applications,''wherein multi-scale computing campaigns comprise …
[图书][B] Artificial intelligence and high-performance computing for accelerating structure-based drug discovery
AR Clyde - 2022 - search.proquest.com
Traditional techniques for discovering novel drugs are too slow for 21st challenges, from
precision oncology to emerging global pandemics. The COVID-19 Pandemic demonstrated …
precision oncology to emerging global pandemics. The COVID-19 Pandemic demonstrated …
An Effective Pipeline for Training Variational Autoencoders for Synthesizable and Optimized Molecular Design
FH Mozumder, BJ Yoon - IEEE Access, 2024 - ieeexplore.ieee.org
Variational auto-encoders (VAE) for molecular design and optimization have gained
popularity due to their efficiency in exploring high-dimensional molecular space to identify …
popularity due to their efficiency in exploring high-dimensional molecular space to identify …
Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders
In recent years, deep generative models have been successfully adopted for various
molecular design tasks, particularly in the life and material sciences. A critical challenge for …
molecular design tasks, particularly in the life and material sciences. A critical challenge for …
Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars
In a post-ChatGPT world, this paper explores the potential of leveraging scalable artificial
intelligence for scientific discovery. We propose that scaling up artificial intelligence on high …
intelligence for scientific discovery. We propose that scaling up artificial intelligence on high …
Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials
As global interest in renewable energy continues to increase, there has been a pressing
need for developing novel energy storage devices based on organic electrode materials that …
need for developing novel energy storage devices based on organic electrode materials that …
Decision-Making Under Uncertainty for Multi-stage Pipelines: Simulation Studies to Benchmark Screening Strategies
KG Reyes, J Liu, CJD Vargas - JOM, 2022 - Springer
Multi-stage screening pipelines are ubiquitous throughout experimental and computational
science. Much of the effort in developing screening pipelines focuses on improving …
science. Much of the effort in developing screening pipelines focuses on improving …