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Workshop
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Fri 8:50
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Accelerated Sampling of Rare Events using a Neural Network Bias Potential
Xinru Hua · Rasool Ahmad · Jose Blanchet · Wei Cai
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Workshop
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Unleashing the Potential of Fractional Calculus in Graph Neural Networks
Qiyu Kang · Kai Zhao · Qinxu Ding · Feng Ji · Xuhao Li · WENFEI LIANG · Yang Song · Wee Peng Tay
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Workshop
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Exploring the Potential of Large Language Models (LLMs) in Learning on Graph
Zhikai Chen · Haitao Mao · Hang Li · Wei Jin · Hongzhi Wen · Xiaochi Wei · Shuaiqiang Wang · Dawei Yin · Wenqi Fan · Hui Liu · Jiliang Tang
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Workshop
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Data Distillation for Neural Network Potentials toward Foundational Dataset
Gang Seob Jung · Sangkeun Lee · Jong Choi
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Workshop
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Role of Structural and Conformational Diversity for Machine Learning Potentials
Nikhil Shenoy · Prudencio Tossou · Emmanuel Noutahi · Hadrien Mary · Dominique Beaini · Jiarui Ding
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Workshop
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Sat 12:02
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Simulating the Air Quality Impact of Prescribed Fires Using a Graph Neural Network-Based PM2.5 Emissions Forecasting System
Kyleen Liao · Jatan Buch · Kara Lamb · Pierre Gentine
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Workshop
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Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
Yinbin Han · Meisam Razaviyayn · Renyuan Xu
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Workshop
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Simulating the Air Quality Impact of Prescribed Fires Using a Graph Neural Network-Based PM2.5 Emissions Forecasting System
Kyleen Liao · Jatan Buch · Kara Lamb · Pierre Gentine
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Poster
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Wed 15:00
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GraphMP: Graph Neural Network-based Motion Planning with Efficient Graph Search
Xiao Zang · Miao Yin · Jinqi Xiao · Saman Zonouz · Bo Yuan
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Workshop
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Fri 7:50
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Investigating extrapolation and low-data challenges via contrastive learning of chemical compositions
Federico Ottomano · Giovanni De Felice · Rahul Savani · Vladimir Gusev · Matthew Rosseinsky
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Workshop
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Symmetry Breaking and Equivariant Neural Networks
Oumar Kaba · Siamak Ravanbakhsh
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Workshop
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Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
Bach Nguyen · Truong Son Hy · Long Tran-Thanh · Nhung Nghiem
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