Work

Tackling the Nonlinearity Problem in Inverse Modeling: Mixture Density Network-Backed Quantized AutoEncoder

Year: 2024

Type: conference-paper

Source: International Conference on Machine Learning and Applications

DOI: 10.1109/icmla61862.2024.00148

Authors: Muhammed Nur Talha Kilic, Yuwei Mao, Vishu Gupta, Alok Choudhary, Wei-keng Liao, Ankit Agrawal

Institution: Northwestern University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Science Foundation, U.S. Department of Energy, U.S. Department of Commerce, Northwestern University, National Institute of Standards and Technology, Center for Hierarchical Materials Design

Awards: RAPIDS2: A SCIDAC INSTITUTE FOR COMPUTER SCIENCE, DATA, AND ARTIFICIAL INTELLIGENCE, Collaborative Research: AI-Driven Multi-Scale Design of Materials under Processing Constraints, G2797879381

OpenAlex ID: W4408146364

FWCI:

Cites: 15

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Related to: 10