1 code implementation • 29 Apr 2024 • Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, Chandan K Reddy
Mathematical equations have been unreasonably effective in describing complex natural phenomena across various scientific disciplines.
2 code implementations • 3 Oct 2023 • Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, Amir Barati Farimani
To bridge the gap, we introduce SNIP, a Symbolic-Numeric Integrated Pre-training model, which employs contrastive learning between symbolic and numeric domains, enhancing their mutual similarities in the embeddings.
1 code implementation • NeurIPS 2023 • Parshin Shojaee, Kazem Meidani, Amir Barati Farimani, Chandan K. Reddy
Unlike conventional decoding strategies, TPSR enables the integration of non-differentiable feedback, such as fitting accuracy and complexity, as external sources of knowledge into the transformer-based equation generation process.
1 code implementation • 26 May 2022 • Zijie Li, Kazem Meidani, Amir Barati Farimani
Data-driven learning of partial differential equations' solution operators has recently emerged as a promising paradigm for approximating the underlying solutions.
no code implementations • 26 Jan 2022 • Parand Akbari, Francis Ogoke, Ning-Yu Kao, Kazem Meidani, Chun-Yu Yeh, William Lee, Amir Barati Farimani
In this work, we introduced a comprehensive framework for benchmarking ML for melt pool characterization.
1 code implementation • 6 Dec 2021 • Zijie Li, Kazem Meidani, Prakarsh Yadav, Amir Barati Farimani
Molecular Dynamics (MD) simulation is a powerful tool for understanding the dynamics and structure of matter.
no code implementations • 3 Dec 2020 • Francis Ogoke, Kazem Meidani, Amirreza Hashemi, Amir Barati Farimani
The ability of the method to predict global properties from spatially irregular measurements with high accuracy is demonstrated by predicting the drag force associated with laminar flow around airfoils from scattered velocity measurements.
no code implementations • 20 Oct 2020 • Kazem Meidani, Amir Barati Farimani
Many scientific phenomena are modeled by Partial Differential Equations (PDEs).