I’m really excited about this work led by @ishume.bsky.social :)
We introduce Grinch, a framework that uses GFlowNets to construct quantum optical circuit graphs from the bottom up, edge-by-edge.
📜: arxiv.org/abs/2609.08073
#AIForScience #ML4Phys
I’m really excited about this work led by @ishume.bsky.social :)
We introduce Grinch, a framework that uses GFlowNets to construct quantum optical circuit graphs from the bottom up, edge-by-edge.
📜: arxiv.org/abs/2609.08073
#AIForScience #ML4Phys
We propose Meta-Learning Fourier Neural Operators to approximate inverse Hessians for variational data assimilation.
We propose Meta-Learning Fourier Neural Operators to approximate inverse Hessians for variational data assimilation.
📃 doi.org/10.48550/arXiv…
@ishume94
📃 doi.org/10.48550/arXiv…
@ishume94
(Left: direct simulation; Right: our framework)
Check out our latest results @NeurIPSConf @ML4PhyS on Dec. 15!
(Left: direct simulation; Right: our framework)
Check out our latest results @NeurIPSConf @ML4PhyS on Dec. 15!
#NeurIPS2024 #ml4ps2024 #ml4phys #compchem
#NeurIPS2024 #ml4ps2024 #ml4phys #compchem
📝: arxiv.org/abs/2410.16041
We employed GFlowNets to generate groupings of molecular Hamiltonians aimed to reduce the required number of measurements. 🧑💻
#compchem #quantumcomputing #chemsky
📝: arxiv.org/abs/2410.16041
We employed GFlowNets to generate groupings of molecular Hamiltonians aimed to reduce the required number of measurements. 🧑💻
#compchem #quantumcomputing #chemsky