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Argonne researchers shape the future of AI and machine learning at NeurIPS 2024.

Researchers from Argonne National Laboratory’s Mathematics and Computer Science Division will bring their expertise, insights, and new ideas to the Neural Information Processing Systems (NeurIPS) 2024 Conference!

NeuroIPS, hosted in Vancouver  this year, brings together some of the sharpest minds and thought leaders in artificial intelligence and machine learning for a week of collaboration and intellectual exchange. 

Explore Argonne’s contributions to NeurIPS 2024:  
Names bolded in recognition of Argonne researchers  

December 12

  • Scaling transformer neural networks for skillful and reliable medium-range weather forecasting 
    Poster 
    December 12, 2024 
    11 a.m. – 2 p.m. PST 

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    Presenters: Nguyen Tung, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, Sandeep Madireddy, and Aditya Grover.  
     

December 13

  • SparseLLM: Towards Global Pruning of Pre-trained Language Models 
    Poster Session 
    December 13, 2024 
    11 a.m. – 2 p.m. PST 

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    Presenters: Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, and Liang Zhao. 
     

December 14

  • Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks 
    Workshop : Statistical Frontiers in LLMs and Foundation Models 
    December 14, 2024 

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    Presenters: Chen, Zizhang, Pengyu Hong, Sandeep Madireddy

  • A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners 
    Workshop: NeurIPS 2024 Workshop on Statistical Foundations of LLMs and Foundation Models (SFLLM)  
    December 14, 2024 
     
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    Presenters: Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, Xiaomeng Wang, Tanwi Mallick, Weijie J Su, Camillo Jose Taylor, Dan Roth 

  • Now how do I make this? AI for materials synthesis and manufacturing 
    Workshop: Invited Talk – AI for Accelerated Materials Design Workshop 
    December 14, 2024 
    3:30 –  3:45 p.m. PST 

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    Presenter: Angel Yanguas-Gil 

  • Atomic Layer Deposition Optimization via Targeted Adaptive Design  
    Workshop: Bayesian Decision-making and Uncertainty: from probabilistic and spatiotemporal modeling to sequential experiment design 
    December 14, 2024 

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    Presenters:  Marieme Ngom, Carlo Graziani, Noah Paulson  

  • Machine Learning and the Physical Sciences Workshop 
    Argonne Reviewers: Sandeep Madireddy
     

December 15

  • From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption 
    Workshop: Paper Spotlight – Time Series in the Age of Large Models Workshop 
    December 15, 2024 

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    Presenters:Shourya Bose, Yijiang Li, Amy Van Sant, Yu Zhang, and Kibaek Kim.

  • Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification  
    Workshop: Machine Learning and the Physical Sciences 
    December 15, 2024 

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    Presenters:Canberk Ekmekci, Tekin Bicer, Zichao (Wendy) Di, Junjing Deng, Mujdat Cetin 

  • WildfireGPT: Tailored Large Language Model for Wildfire Analysis 
    Workshop: Tackling Climate Change with Machine Learning Workshop  
    December 15, 2024 

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    Presenters:Yangxinyu Xie, Bowen Jiang, Tanwi Mallick, Joshua David Bergerson, John K. Hutchison, Duane R. Verner, Jordan Branham, M. Ross Alexander, Robert B. Ross, Yan Feng, Leslie-Anne Levy, Weijie Su, Camillo J. Taylor 

Argonne National Laboratory seeks solutions to pressing national problems in science and technology by conducting leading-edge basic and applied research in virtually every scientific discipline. Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.

The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://​ener​gy​.gov/​s​c​ience.