Tess Smidt

Presentation History

2024 MRS Fall Meeting & Exhibit

Quantifying Chemical Short-Range Order in Metallic Alloys

Dec 6, 2024, 9:15 AM

2023 MRS Fall Meeting

Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Generating Molecules

Dec 1, 2023, 10:30 AM

2023 MRS Fall Meeting

Using Symmetry-Equivariant Neural Networks (ENNs) to Uncover Symmetry-Implied Missing Information

Nov 28, 2023, 4:00 PM

2023 MRS Fall Meeting

Exploration of Machine Learning (ML) Methods for Determining Unit Cell Parameters from Powder XRD Patterns

Nov 28, 2023, 2:15 PM

2023 MRS Fall Meeting

Machine Learning of Magnetoelectric Multipoles

Nov 28, 2023, 2:00 PM

2023 MRS Fall Meeting

Harnessing the Properties of Equivariant Neural Networks to Understand and Design Materials

Nov 28, 2023, 10:00 AM

2023 MRS Fall Meeting

Leveraging Density Functional Theory in the Design of Novel Metal Organic Chalcogenide Assemblies (MOChAs)

Nov 28, 2023, 8:45 AM

2023 MRS Fall Meeting

Bispectral Analysis of Local Atomic Environments in Metal-Organic Chalcogenide Assemblies and Related Material Classes

Nov 27, 2023, 11:15 AM

2022 MRS Spring Meeting

NequIP—Equivariance Enables Machine Learning Interatomic Potentials at Unprecedented Sample Efficiency and Accuracy

May 10, 2022, 9:00 AM

2021 MRS Fall Meeting

NequIP—E(3)-Equivariant Convolutions Enable Sample-Efficient, Scalable and Highly Accurate Machine Learning Interatomic Potentials

Dec 2, 2021, 1:45 PM

2021 MRS Fall Meeting

Euclidean Symmetry in Machine Learning for Materials Science

Nov 29, 2021, 8:30 AM

2019 MRS Fall Meeting

Learning Direct, Symmetry-Preserving and Efficient Force-Fields with Tensor-Field Neural Networks

Dec 3, 2019, 9:45 AM

2019 MRS Spring Meeting

Strongly Quantum Confined Excitons in 2D Layered Hybrid Metal Chalcogenolate Multi Quantum Wells

Apr 24, 2019, 1:45 PM