Search Results - Shoghi, Nima

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  1. 1
    Transfer learning using attentions across atomic systems with graph neural networks (TAAG)

    Transfer learning using attentions across atomic systems with graph neural networks (TAAG) by Kolluru, Adeesh, Shoghi, Nima, Shuaibi, Muhammed, Goyal, Siddharth, Das, Abhishek, Zitnick, C. Lawrence, Ulissi, Zachary

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  2. 2
    Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery

    Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery by Kolluru, Adeesh, Shuaibi, Muhammed, Palizhati, Aini, Shoghi, Nima, Das, Abhishek, Wood, Brandon, Zitnick, C. Lawrence, Kitchin, John R., Ulissi, Zachary W.

    Published in ACS catalysis
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  3. 3
    The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts

    The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts by Tran, Richard, Lan, Janice, Shuaibi, Muhammed, Wood, Brandon M., Goyal, Siddharth, Das, Abhishek, Heras-Domingo, Javier, Kolluru, Adeesh, Rizvi, Ammar, Shoghi, Nima, Sriram, Anuroop, Therrien, Félix, Abed, Jehad, Voznyy, Oleksandr, Sargent, Edward H., Ulissi, Zachary, Zitnick, C. Lawrence

    Published in ACS catalysis
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  4. 4
    Context-Aware Task Handling in Resource-Constrained Robots with Virtualization

    Context-Aware Task Handling in Resource-Constrained Robots with Virtualization by Hadidi, Ramyad, Ghaleshahi, Nima Shoghi, Asgari, Bahar, Kim, Hyesoon

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  5. 5
    SmaQ: Smart Quantization for DNN Training by Exploiting Value Clustering

    SmaQ: Smart Quantization for DNN Training by Exploiting Value Clustering by Shoghi, Nima, Bersatti, Andrei, Qureshi, Moinuddin, Kim, Hyesoon

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  6. 6
    Distribution Learning for Molecular Regression

    Distribution Learning for Molecular Regression by Shoghi, Nima, Shoghi, Pooya, Anuroop Sriram, Das, Abhishek

    Published in arXiv.org
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  7. 7
    From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction

    From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction by Shoghi, Nima, Adeesh Kolluru, Kitchin, John R, Ulissi, Zachary W, Zitnick, C Lawrence, Wood, Brandon M

    Published in arXiv.org
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  8. 8
    The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts

    The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts by Tran, Richard, Lan, Janice, Shuaibi, Muhammed, Wood, Brandon M, Goyal, Siddharth, Das, Abhishek, Heras-Domingo, Javier, Adeesh Kolluru, Rizvi, Ammar, Shoghi, Nima, Anuroop Sriram, Therrien, Felix, Abed, Jehad, Voznyy, Oleksandr, Sargent, Edward H, Ulissi, Zachary, Zitnick, C Lawrence

    Published in arXiv.org
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  9. 9
    Context-Aware Task Handling in Resource-Constrained Robots with Virtualization

    Context-Aware Task Handling in Resource-Constrained Robots with Virtualization by Hadidi, Ramyad, Nima Shoghi Ghalehshahi, Asgari, Bahar, Kim, Hyesoon

    Published in arXiv.org
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  10. 10
    Secure Location-Aware Authentication and Communication for Intelligent Transportation Systems

    Secure Location-Aware Authentication and Communication for Intelligent Transportation Systems by Nima Shoghi Ghalehshahi, Hadidi, Ramyad, Lee, Jaewon, Chen, Jun, Siqueria, Arthur, Rajan, Rahul, Dhawan, Shaan, Pooya Shoghi Ghalehshahi, Kim, Hyesoon

    Published in arXiv.org
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  11. 11
    Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery

    Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery by Adeesh Kolluru, Shuaibi, Muhammed, Palizhati, Aini, Shoghi, Nima, Das, Abhishek, Wood, Brandon, Zitnick, C Lawrence, Kitchin, John R, Ulissi, Zachary W

    Published in arXiv.org
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  12. 12
    Patients' Lived Experiences of the Paternalistic Care Behavior: A Qualitative study

    Patients' Lived Experiences of the Paternalistic Care Behavior: A Qualitative study by Pourgholam, Nima, Shoghi, Mahnaz, Borimnejad, Leili

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