1 code implementation • 31 Oct 2023 • Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows.
1 code implementation • 29 Sep 2023 • Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
Molecular Representation Learning (MRL) has proven impactful in numerous biochemical applications such as drug discovery and enzyme design.
no code implementations • 6 Dec 2021 • Alexander Lavin, David Krakauer, Hector Zenil, Justin Gottschlich, Tim Mattson, Johann Brehmer, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atılım Güneş Baydin, Carina Prunkl, Brooks Paige, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob Macke, Kyle Cranmer, Jiaxin Zhang, Haruko Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer
We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence.
no code implementations • 20 Nov 2019 • Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A. Winkler, Joe Shapter, Michael J. Ford
The screening of novel materials is an important topic in the field of materials science.
2 code implementations • 31 May 2019 • Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev
Designing new molecules with a set of predefined properties is a core problem in modern drug discovery and development.
Ranked #1 on Molecular Graph Generation on MOSES
3 code implementations • 28 Jan 2018 • Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg
In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials.
1 code implementation • 29 Nov 2017 • Mariya Popova, Olexandr Isayev, Alexander Tropsha
In the first phase of the method, generative and predictive models are trained separately with a supervised learning algorithm.
no code implementations • 16 Aug 2017 • Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
One of the grand challenges in modern theoretical chemistry is designing and implementing approximations that expedite ab initio methods without loss of accuracy.
1 code implementation • 27 Oct 2016 • Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
Deep learning is revolutionizing many areas of science and technology, especially image, text and speech recognition.
Chemical Physics