copernicAI: Geometric AI for spherical data

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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.

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Publications

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

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

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Efficient generalized spherical CNNs

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Talks

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

Jul 2024 University of Hull
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Scientific AI for the Physical Sciences

Jul 2024 UCL
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Statistical characterization and generative modelling of cosmological fields

Jul 2024 UCL
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Wide-field, field-level compression for simulation-based inference (SBI) for Euclid cosmic shear

Jun 2024 Rome
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Geometric deep learning on the sphere for the physical sciences

Jul 2023 London
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Scalable and equivariant spherical CNNs by discrete-continuous (DISCO) convolutions

May 2023 Virtual
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Geometric deep learning on the sphere: scalable and equivariant spherical CNNs

Oct 2022 CEA Saclay
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Geometric deep learning on the sphere: scalable and equivariant spherical CNNs

Sep 2022 Cambridge
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A brief introduction to geometric deep learning

May 2022 UCL
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Geometric deep learning on the sphere: spherical CNNs and scattering networks

Apr 2022 Harwell (Remote)
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Scattering networks on the sphere for scalable and rotationally equivariant spherical CNNs

Apr 2022 Virtual
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Efficient generalized spherical CNNs

May 2021 Virtual
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Geometric deep learning on the sphere: efficient generalized spherical CNNs

Apr 2021 London
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Geometric deep learning on the sphere: efficient generalized spherical CNNs

Mar 2021 London
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Deep learning on the celestial sphere

Dec 2020 London
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Geometric deep learning on the sphere: efficient generalized spherical CNNs

Nov 2020 London
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Geometric deep learning on the sphere: efficient generalized spherical CNNs

Oct 2020 London
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