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Poster
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Tue 14:00
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Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems
Abishek Thangamuthu · Gunjan Kumar · Suresh Bishnoi · Ravinder Bhattoo · N M Anoop Krishnan · Sayan Ranu
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Poster
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Tue 14:00
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Hamiltonian Latent Operators for content and motion disentanglement in image sequences
Asif Khan · Amos Storkey
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Poster
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Thu 14:00
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Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data
Yusuke Tanaka · Tomoharu Iwata · naonori ueda
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Poster
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Thu 14:00
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Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space
Yunbum Kook · Yin-Tat Lee · Ruoqi Shen · Santosh Vempala
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Poster
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Wed 14:00
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Bayesian inference via sparse Hamiltonian flows
Naitong Chen · Zuheng Xu · Trevor Campbell
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Poster
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Wed 9:00
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Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
Ignacio Peis · Chao Ma · José Miguel Hernández-Lobato
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Poster
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Fixed-Distance Hamiltonian Monte Carlo
Hadi Mohasel Afshar · Sally Cripps
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Poster
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Thu 9:00
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Sparse Gaussian Process Hyperparameters: Optimize or Integrate?
Vidhi Lalchand · Wessel Bruinsma · David Burt · Carl Edward Rasmussen
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Poster
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Thu 14:00
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Alternating Mirror Descent for Constrained Min-Max Games
Andre Wibisono · Molei Tao · Georgios Piliouras
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Workshop
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Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
Oswin So · Gongjie Li · Evangelos Theodorou · Molei Tao
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Workshop
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Identifying Hamiltonian Manifold in Neural Networks
Yeongwoo Song · Hawoong Jeong
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Workshop
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Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation
Di Luo · Shunyue Yuan · James Stokes · Bryan Clark
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