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Found 10 papers, 4 papers with code
Equilibrium Aggregation: Encoding Sets via Optimization
Processing sets or other unordered, potentially variable-sized inputs in neural networks is usually handled by aggregating a number of input tensors into a single representation.
Universal Approximation of Functions on Sets
We provide a theoretical analysis of Deep Sets which shows that this universal approximation property is only guaranteed if the model's latent space is sufficiently high-dimensional.
E(n) Equivariant Normalizing Flows
This paper introduces a generative model equivariant to Euclidean symmetries: E(n) Equivariant Normalizing Flows (E-NFs).
Iterative SE(3)-Transformers
Motivated by this application, we implement an iterative version of the SE(3)-Transformer, an SE(3)-equivariant attention-based model for graph data.
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
We introduce the SE(3)-Transformer, a variant of the self-attention module for 3D point clouds and graphs, which is equivariant under continuous 3D roto-translations.
Improving End-to-End Object Tracking Using Relational Reasoning
Relational reasoning, the ability to model interactions and relations between objects, is valuable for robust multi-object tracking and pivotal for trajectory prediction.
End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning
The majority of contemporary object-tracking approaches do not model interactions between objects.
On the Limitations of Representing Functions on Sets
Recent work on the representation of functions on sets has considered the use of summation in a latent space to enforce permutation invariance.
Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes
Conversely, training on an easy dataset where visual cues are positively correlated with stability, the baseline model learns a bias leading to poor performance on a harder dataset.
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
Physical intuition is pivotal for intelligent agents to perform complex tasks.
