3 citations · 4 across the 9 of their papers we have counts for
10 papers
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…
Fast Volume Alignment by Frequency-Marched Newton Method
Fabian Kruse, Valentin Debarnot, Vinith Kishore +1
We introduce Matcha, a fast method for rotational pose estimation in three-dimensional alignment, and combine it with FFT-based translation updates for full pose estimation. Classi…
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,…
Gaussian Surrogates for Poisson Imaging: Some Theoretical and Empirical Results
Alexandra Spitzer, Lorenzo Baldassari, Valentin Debarnot +2
In imaging inverse problems with Poisson-distributed measurements, it is common to use objectives derived from the Poisson likelihood. But performance is often evaluated by mean sq…
Rates and architectures for learning geometrically non-trivial operators
T. Mitchell Roddenberry, Leo Tzou, Ivan Dokmanić +2
Deep learning methods have proven capable of recovering operators between high-dimensional spaces, such as solution maps of PDEs and similar objects in mathematical physics, from v…
Beyond Exhaustive Sampling: Efficient Rotational Matching via Ball Harmonics
Fabian Kruse, Vinith Kishore, Valentin Debarnot +1
Cryo-ET allows to generate tomograms of biological samples in situ, capturing complex structures in their native context. Despite low signal-to-noise ratio in reconstructed volumes…
Localized Supervised Learning for Cryo-ET Reconstruction
Vinith Kishore, Valentin Debarnot, AmirEhsan Khorashadizadeh +1
Cryo-electron tomography (Cryo-ET) is a powerful tool in structural biology for 3D visualization of cells and biological systems at resolutions sufficient to identify individual pr…
CryoLithe: Rapid Cryo-ET Reconstruction via Transform-Localized Deep Learning
Vinith Kishore, Valentin Debarnot, AmirEhsan Khorashadizadeh +3
Cryo-electron tomography (cryo-ET) enables 3D visualization of cellular structures. Accurate reconstruction of high-resolution volumes is complicated by the very low signal-to-nois…
LoFi: Neural Local Fields for Scalable Image Reconstruction
AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu +2
Neural fields or implicit neural representations (INRs) have attracted significant attention in computer vision and imaging due to their efficient coordinate-based representation o…
SeisLM: a Foundation Model for Seismic Waveforms
Tianlin Liu, Jannes Münchmeyer, Laura Laurenti +3
We introduce the Seismic Language Model (SeisLM), a foundational model designed to analyze seismic waveforms -- signals generated by Earth's vibrations such as the ones originating…