Suchergebnisse - Pathak, Jay

Hamiltonian Simulation for Advection-Diffusion Equation with arbitrary transport field von Gomes, Niladri, Sharma, Gautam, Pathak, Jay

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One-shot learning for solution operators of partial differential equations von Jiao, Anran, He, Haiyang, Ranade, Rishikesh, Pathak, Jay, Lu, Lu

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CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design von Govindarajan, Prashant, Baldelli, Davide, Pathak, Jay, Fournier, Quentin, Chandar, Sarath

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Hybrid Iterative Solvers with Geometry-Aware Neural Preconditioners for Parametric PDEs von Lee, Youngkyu, Florencio, Francesc Levrero, Pathak, Jay, Karniadakis, George Em

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NSPOD: Accelerating Krylov solvers via DeepONet-learned POD subspaces von Levrero-Florencio, Francesc, Lee, Youngkyu, Pathak, Jay, Karniadakis, George Em

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Sampling-based Distributed Training with Message Passing Neural Network von Kakka, Priyesh, Nidhan, Sheel, Ranade, Rishikesh, Pathak, Jay, MacArt, Jonathan F.

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A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations von Nidhan, Sheel, Jiang, Haoliang, Ghule, Lalit, Umphrey, Clancy, Ranade, Rishikesh, Pathak, Jay

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Hardware Realization of a Hamiltonian Simulation Algorithm for Time-Domain Maxwells Equations von Sharma, Gautam, Tiwari, Apurva, Gomes, Niladri, Jojo, Jezer, Bracken, J. Eric, Pathak, Jay

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Algorithmic Advances Towards a Realizable Quantum Lattice Boltzmann Method von Tiwari, Apurva, Iaconis, Jason, Jojo, Jezer, Ray, Sayonee, Roetteler, Martin, Hill, Chris, Pathak, Jay

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Blending Neural Operators and Relaxation Methods in PDE Numerical Solvers von Zhang, Enrui, Kahana, Adar, Kopaničáková, Alena, Turkel, Eli, Ranade, Rishikesh, Pathak, Jay, Karniadakis, George Em

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Quantum Lattice Boltzmann Solutions for Transport under 3D Spatially Varying Advection on Trapped Ion Hardware von Ray, Sayonee, Jojo, Jezer, Iaconis, Jason, Gnanasekaran, Abeynaya, Tiwari, Apurva, Roetteler, Martin, Hill, Chris, Pathak, Jay

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Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem von Lee, Youngkyu, Liu, Shanqing, Zou, Zongren, Kahana, Adar, Turkel, Eli, Ranade, Rishikesh, Pathak, Jay, Karniadakis, George Em

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Accelerating large-scale linear algebra using variational quantum imaginary time evolution von Aboumrad, Willie, Zhu, Daiwei, Girotto, Claudio, Rouet, François-Henry, Jojo, Jezer, Lucas, Robert, Pathak, Jay, Kaushik, Ananth, Roetteler, Martin

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