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Workshop
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The Pairwise Prony Algorithm: Efficient Inference of Stochastic Block Models with Prescribed Subgraph Densities
Lee M Gunderson · Gecia Bravo-Hermsdorff · Peter Orbanz
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Poster
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Wed 17:00
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Personalized Federated Learning with Inferred Collaboration Graphs
Rui Ye · Zhenyang Ni · Fangzhao Wu · Siheng Chen · Yan-Feng Wang
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Workshop
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Geometric Constraints in Probabilistic Manifolds: A Bridge from Molecular Dynamics to Structured Diffusion Processes
Justin Diamond · Markus Lill
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Workshop
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Dimensionality Reduction as Probabilistic Inference
Aditya Ravuri · Francisco Vargas · Vidhi Ramesh · Neil Lawrence
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Poster
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Thu 16:30
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Effective and Efficient Structural Inference with Reservoir Computing
Aoran Wang · Tsz Pan Tong · Jun Pang
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Poster
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Tue 14:00
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ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval
Kexun Zhang · Xianjun Yang · William Wang · Lei Li
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Poster
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Wed 17:00
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Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao · Menglei Chai · Minchen Li · Chenfanfu Jiang
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Workshop
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The Local Inconsistency Resolution Algorithm
Oliver Richardson
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Poster
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Tue 17:00
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Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian
Haiyang Yu · Zhao Xu · Xiaofeng Qian · Xiaoning Qian · Shuiwang Ji
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Workshop
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The Local Inconsistency Resolution Algorithm
Oliver Richardson
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Workshop
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Sat 14:25
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Efficiently Scaling Transformer Inference (Aakanksha Chowdhery, Google Research)
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Poster
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Thu 16:30
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Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
Joonhyuk Yang · Dongpil Shin · Hye Won Chung
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