172 citations · 1.1k across the 55 of their papers we have counts for
8 papers · 1 filter
Weisfeiler and Leman go Machine Learning: The Story so far
Christopher Morris, Yaron Lipman, Haggai Maron +5
In recent years, algorithms and neural architectures based on the Weisfeiler--Leman algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a powerful…
Frame Averaging for Equivariant Shape Space Learning
Matan Atzmon, Koki Nagano, Sanja Fidler +2
The task of shape space learning involves mapping a train set of shapes to and from a latent representation space with good generalization properties. Often, real-world collections…
Frame Averaging for Invariant and Equivariant Network Design
Omri Puny, Matan Atzmon, Heli Ben-Hamu +4
Many machine learning tasks involve learning functions that are known to be invariant or equivariant to certain symmetries of the input data. However, it is often challenging to de…
Augmenting Implicit Neural Shape Representations with Explicit Deformation Fields
Matan Atzmon, David Novotny, Andrea Vedaldi +1
Implicit neural representation is a recent approach to learn shape collections as zero level-sets of neural networks, where each shape is represented by a latent code. So far, the…
Moser Flow: Divergence-based Generative Modeling on Manifolds
Noam Rozen, Aditya Grover, Maximilian Nickel +1
We are interested in learning generative models for complex geometries described via manifolds, such as spheres, tori, and other implicit surfaces. Current extensions of existing (…
Riemannian Convex Potential Maps
Samuel Cohen, Brandon Amos, Yaron Lipman
Modeling distributions on Riemannian manifolds is a crucial component in understanding non-Euclidean data that arises, e.g., in physics and geology. The budding approaches in this…
Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Representing surfaces as zero level sets of neural networks recently emerged as a powerful modeling paradigm, named Implicit Neural Representations (INRs), serving numerous downstr…
Volume Rendering of Neural Implicit Surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten +1
Neural volume rendering became increasingly popular recently due to its success in synthesizing novel views of a scene from a sparse set of input images. So far, the geometry learn…