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Workshop
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Exploring the Existence of Atmospheric Blocking’s Precursor Patterns with Physics-Informed Explainable AI
Anh Nhu · Lei Wang
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Workshop
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How to Select Physics-Informed Neural Networks in the Absence of Ground Truth: A Pareto Front-Based Strategy
Zhao Wei · Jian Cheng Wong · Nicholas Sung · Abhishek Gupta · Chin Chun Ooi · Pao-Hsiung Chiu · My Ha Dao · Yew Soon ONG
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Workshop
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Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
Usha Bhalla · Suraj Srinivas · Himabindu Lakkaraju
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Workshop
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Physics-Constrained Random Forests for Turbulence Model Uncertainty Estimation
Marcel Matha
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Workshop
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A Machine Learning Pressure Emulator for Hydrogen Embrittlement
Minh Chau · João Almeida · Elie Alhajjar · Alberto Costa Nogueira Junior
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Workshop
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Physics-informed Localized Learning for Advection-Diffusion-Reaction Systems
Surya Sathujoda · Soham Sheth
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Workshop
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Efficient Estimation of Local Robustness of Machine Learning Models
Tessa Han · Suraj Srinivas · Himabindu Lakkaraju
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Workshop
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An Interactive Human-Machine Learning Interface for Collecting and Learning from Complex Annotations
Jonathan Erskine · Raul Santos-Rodriguez · Alexander Hepburn · Matt Clifford
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Workshop
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Fri 12:15
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3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH)
Weina Jin · Ramin Zabih · S. Kevin Zhou · Yuyin Zhou · Xiaoxiao Li · Yifan Peng · Zongwei Zhou · Yucheng Tang · Yuzhe Yang · Agni Kumar
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Workshop
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Seeing Through the Facade: Understanding the Realism, Expressivity, and Limitations of Diffusion Models
Christopher Pondoc · Joseph O'Brien · Joseph Guman
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Workshop
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Unbinned Profiled Unfolding
Jay Chan · Benjamin Nachman
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Workshop
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Identifying Inequity in Treatment Allocation
Yewon Byun · Dylan Sam · Zachary Lipton · Bryan Wilder
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