1.1k citations · 1.2k across the 6 of their papers we have counts for
9 papers · 1 filter
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics
Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang +6
Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accur…
Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models
Daniel D. Johnson, Jacob Austin, Rianne van den Berg +1
Denoising diffusion probabilistic models (DDPMs) have shown impressive results on sequence generation by iteratively corrupting each example and then learning to map corrupted vers…
Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent
Samira Abnar, Rianne van den Berg, Golnaz Ghiasi +3
We focus on the problem of domain adaptation when the goal is shifting the model towards the target distribution, rather than learning domain invariant representations. It has been…
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
Rianne van den Berg, Alexey A. Gritsenko, Mostafa Dehghani +2
In this paper we analyse and improve integer discrete flows for lossless compression. Integer discrete flows are a recently proposed class of models that learn invertible transform…
Differentiable probabilistic models of scientific imaging with the Fourier slice theorem
Karen Ullrich, Rianne van den Berg, Marcus Brubaker +2
Scientific imaging techniques such as optical and electron microscopy and computed tomography (CT) scanning are used to study the 3D structure of an object through 2D observations.…
Integer Discrete Flows and Lossless Compression
Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg +1
Lossless compression methods shorten the expected representation size of data without loss of information, using a statistical model. Flow-based models are attractive in this setti…