Today’s AI techniques have shown remarkable performance and are changing the world in which we live. However, the deep learning techniques that are leading to this AI revolution simply do not work with spherical data.

copernicAI unlocks the remarkable potential of deep learning for problems involving spherical data, in astrophysics, virtual reality and beyond.

## Publications

## Talks

### Towards wide-field, field-level simulation-based inference (SBI) for Euclid cosmic shear

Jul 2024
University of Hull

### Wide-field, field-level compression for simulation-based inference (SBI) for Euclid cosmic shear

Jun 2024
Rome

### Scalable and equivariant spherical CNNs by discrete-continuous (DISCO) convolutions

May 2023
Virtual

### Geometric deep learning on the sphere: scalable and equivariant spherical CNNs

Oct 2022
CEA Saclay

### Geometric deep learning on the sphere: spherical CNNs and scattering networks

Apr 2022
Harwell (Remote)

### Scattering networks on the sphere for scalable and rotationally equivariant spherical CNNs

Apr 2022
Virtual