4 papers
Generative Forecasting from Coarse-Grained Observations: When Does Cascading Help?
Alexandra Spitzer, Giovanni Abati, Lorenzo Baldassari +3
We study probabilistic forecasting of dynamical systems such as fluids and waves from coarse observations. Since the unseen fine scales influence the dynamics, the same coarse init…
Dandelion: A Spherical Flower for Neural Simulation of Planetary Dynamics
Till Muser, Giovanni Abati, Ivan Dokmanić
Many dynamical processes unfold on the sphere but the default scientific machine learning architectures are Euclidean. Applying these architectures on a regular lat-lon grid causes…
Flowers: A Warp Drive for Neural PDE Solvers
Till Muser, Alexandra Spitzer, Matti Lassas +2
We introduce Flowers, a neural architecture for learning PDE solution operators built entirely from multihead warps. Aside from pointwise channel mixing and a multiscale scaffold,…
Provable advantages of kernel-based quantum learners and quantum preprocessing based on Grover's algorithm
Till Muser, Elias Zapusek, Vasilis Belis +1
There is an ongoing effort to find quantum speedups for learning problems. Recently, [Y. Liu et al., Nat. Phys. , 1013--1017 (2021)] have proven an exponential speedup…