Publications

Information Decomposition Diagrams Applied beyond Shannon Entropy: A Generalization of Hu's Theorem

We generalize information diagrams to functions beyond Shannon entropy, including Kolmogorov complexity and the generalization error from machine learning.

Leon Lang, Pierre Baudot, Rick Quax, Patrick Forré

Information Decomposition Diagrams Applied beyond Shannon Entropy: A Generalization of Hu's Theorem

A Program to Build E(N)-Equivariant Steerable CNNs

We propose a general method to implement equivariant convolutional neural networks and demonstrate it for 3D equivariant tasks. The implementation is based on the Wigner-Eckart theorem for steerable kernels.

Gabriele Cesa, Leon Lang, Maurice Weiler

A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels

We generalize the famous Wigner-Eckart theorem from quantum mechanics in order to characterize steerable kernel spaces in representation theoretic terms.

Leon Lang, Maurice Weiler

A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels

Learning to Request Guidance in Emergent Communication

We analyze the training behaviour of an agent that can ask for help. Doing this is costly, and so the agent learns to become more independent in familiar situations.

Benjamin Kolb, Leon Lang, Henning Bartsch, Arwin Gansekoele, Raymond Koopmanschap, Leonardo Romor, David Speck, Mathijs Mul, Elia Bruni

Learning to Request Guidance in Emergent Communication