2 citations · 5 across the 12 of their papers we have counts for
5 papers · 1 filter
Challenges with Differentiable Quantum Dynamics
Sri Hari Krishna Narayanan, Michael Perlin, Robert Lewis-Swan +4
Differentiable quantum dynamics require automatic differentiation of a complex-valued initial value problem, which numerically integrates a system of ordinary differential equation…
Differentiating Through Linear Solvers
Paul Hovland, Jan Hückelheim
Computer programs containing calls to linear solvers are a known challenge for automatic differentiation. Previous publications advise against differentiating through the low-level…
Profiling checkpointing schedules in adjoint ST-AD
Laurent Hascoët, Jean-Luc Bouchot, Shreyas Sunil Gaikwad +2
Checkpointing is a cornerstone of data-flow reversal in adjoint algorithmic differentiation. Checkpointing is a storage/recomputation trade-off that can be applied at different lev…
Parametric Sensitivities of a Wind-driven Baroclinic Ocean Using Neural Surrogates
Yixuan Sun, Elizabeth Cucuzzella, Steven Brus +6
Numerical models of the ocean and ice sheets are crucial for understanding and simulating the impact of greenhouse gases on the global climate. Oceanic processes affect phenomena s…
MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade
Shreyas Sunil Gaikwad, Sri Hari Krishna Narayanan, Laurent Hascoet +6
The Massachusetts Institute of Technology General Circulation Model (MITgcm) is widely used by the climate science community to simulate planetary atmosphere and ocean circulations…