ICML 2026 paper proposing APT, a geometry-/mesh-/physics-agnostic neural operator that fuses graph-based local feature extraction with global attention for long-range physical effects; achieves 4× saturation error reduction on 2D faulted CO2 storage vs prior SOTA, 19,873× speedup over GEOS and 6,800× over ECLIPSE.
arXiv preprint (copyright held by authors)Neural OperatorSubsurface EnergyCO2 Storage
A continental-scale electrical resistivity model of Australia's shallow crust (up to ~650 m depth) derived from probabilistic deep learning inversion of 26.6+ million AEM soundings, with quantified uncertainty for geology, groundwater, and critical mineral exploration.
See LICENSE fileAirborne EMResistivity imagingProbabilistic inversion