Search Results for author: Ethan Herron

Found 4 papers, 1 papers with code

Latent Diffusion Models for Structural Component Design

no code implementations20 Sep 2023 Ethan Herron, Jaydeep Rade, Anushrut Jignasu, Baskar Ganapathysubramanian, Aditya Balu, Soumik Sarkar, Adarsh Krishnamurthy

Specifically, we employ a Latent Diffusion model to generate potential designs of a component that can satisfy a set of problem-specific loading conditions.

Image Generation

Neural PDE Solvers for Irregular Domains

no code implementations7 Nov 2022 Biswajit Khara, Ethan Herron, Zhanhong Jiang, Aditya Balu, Chih-Hsuan Yang, Kumar Saurabh, Anushrut Jignasu, Soumik Sarkar, Chinmay Hegde, Adarsh Krishnamurthy, Baskar Ganapathysubramanian

Neural network-based approaches for solving partial differential equations (PDEs) have recently received special attention.

Cross-Gradient Aggregation for Decentralized Learning from Non-IID data

1 code implementation2 Mar 2021 Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar

Inspired by ideas from continual learning, we propose Cross-Gradient Aggregation (CGA), a novel decentralized learning algorithm where (i) each agent aggregates cross-gradient information, i. e., derivatives of its model with respect to its neighbors' datasets, and (ii) updates its model using a projected gradient based on quadratic programming (QP).

Continual Learning

Algorithmically-Consistent Deep Learning Frameworks for Structural Topology Optimization

no code implementations9 Dec 2020 Jaydeep Rade, Aditya Balu, Ethan Herron, Jay Pathak, Rishikesh Ranade, Soumik Sarkar, Adarsh Krishnamurthy

We achieve this by training multiple networks, each learning a different step of the overall topology optimization methodology, making the framework more consistent with the topology optimization algorithm.

BIG-bench Machine Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.