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Found 6 papers, 4 papers with code
$ρ$-Diffusion: A diffusion-based density estimation framework for computational physics
In physics, density $\rho(\cdot)$ is a fundamentally important scalar function to model, since it describes a scalar field or a probability density function that governs a physical process.
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling
We propose MatSci ML, a novel benchmark for modeling MATerials SCIence using Machine Learning (MatSci ML) methods focused on solid-state materials with periodic crystal structures.
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
We present the Open MatSci ML Toolkit: a flexible, self-contained, and scalable Python-based framework to apply deep learning models and methods on scientific data with a specific focus on materials science and the OpenCatalyst Dataset.
A rotational and vibrational investigation of phenylpropiolonitrile (C$_6$H$_5$C$_3$N)
The evidence for benzonitrile (C$_6$H$_5$CN}) in the starless cloud core TMC-1 makes high-resolution studies of other aromatic nitriles and their ring-chain derivatives especially timely.
Astrophysics of Galaxies Chemical Physics
Discovery of Interstellar trans-cyanovinylacetylene (HCCCH=CHCN) and vinylcyanoacetylene (H$_2$C=CHC$_3$N) in GOTHAM Observations of TMC-1
We report the discovery of two unsaturated organic species, trans-(E)-cyanovinylacetylene and vinylcyanoacetylene, using the second data release of the GOTHAM deep survey towards TMC-1 with the 100 m Green Bank Telescope.
Astrophysics of Galaxies
Molecule Identification with Rotational Spectroscopy and Probabilistic Deep Learning
A proof-of-concept framework for identifying molecules of unknown elemental composition and structure using experimental rotational data and probabilistic deep learning is presented.
Chemical Physics
