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Instances

An instance is a complete, reproducible inverse problem: a config dataclass in which every paper number is a field, scene generators with difficulty classes, an independent high-fidelity data generator, the problem builder, a default curriculum, metrics and baselines. The CLI, the benchmark harness, the diagnostics, the auto-tuner and the gallery all work on any instance, including your own (A new instance).

nefi list instances -v               # the registry: scene classes, baselines, metrics, configs
nefi run <name> --smoke              # seconds on a CPU
nefi run configs/<name>_full.yaml --device cuda
nefi bench <name> --methods neural,grid --classes all --n 8 --seeds 0,1,2

The papers

instance problem unknown physics measurement
nv_relaxometry NeTMY — NV-center noise sensing spin density ρ ≥ 0 and Larmor field ωL (2-D) dipolar tensor power kernel × Lorentzian (F2) noise spectra, 50 frequencies × 64²
thermal_tomography NeFTY — pulsed-thermography tomography diffusivity α ∈ [αmin, αmax] (3-D) implicit-Euler heat equation, discrete adjoint 100 surface frames × 64²

Classic imaging

instance problem unknown physics measurement
toy1d 1-D deblurring (tutorial, CI) signal x ≥ 0 FFT Gaussian blur 128 samples
deconvolution image deblurring, Gaussian or Poisson noise image x ≥ 0 FFT convolution (Gaussian / motion / disk PSF) blurred image
sparse_view_ct sparse-view and limited-angle CT attenuation μ ∈ [0, 1] differentiable Radon transform sinogram, 20 views

Elliptic PDEs

instance problem unknown physics measurement
poisson_source source recovery source f ≥ 0 −κΔu = f, spectral solver potential on 10 % of pixels, a boundary strip or all
eit electrical impedance tomography conductivity σ −∇·(σ∇u) = 0, implicit-function adjoint boundary voltages of current patterns
darcy_flow hydraulic tomography log-permeability −∇·(k∇p) = q, implicit-function adjoint well-gauge pressures, 6 configurations
current_density NV current imaging stream function of a sheet current planar magnetostatics (FFT) stray field Bz

Wave, optics and reaction

instance problem unknown physics measurement
wave_fwi full-waveform inversion sound speed c acoustic wave equation, leapfrog + PML shot gathers
diffraction_tomography optical diffraction tomography scattering contrast χ Born / Rytov scattering complex fields, 16 angles × 64 receivers
holography inline phase retrieval phase φ angular-spectrum propagation intensities at 3 distances
reaction_diffusion Gray–Scott parameter inversion feed-rate field F reaction–diffusion time stepping 4 snapshots of both species

Volumetric (3-D)

instance problem unknown physics measurement
ct3d 3-D sparse-view CT attenuation μ(x, y, z) slice-stacked Radon transform sinogram stack, 30 views
deconvolution3d fluorescence z-stack deconvolution fluorophore density 3-D FFT convolution, elongated PSF blurred z-stack
dot3d diffuse optical tomography absorption μa diffusion equation, Robin boundaries, implicit-function adjoint top-face reflectance, 3 × 3 sources
photoacoustic3d photoacoustic tomography initial pressure p0 3-D wave equation, sponge layer traces of a 16 × 16 planar array

thermal_tomography is volumetric as well; with the four systems above it forms the 3-D showcase.

Every instance page has

  • At a glance — the problem, the unknown, the physics, the measurement, the difficulty classes, the baselines, the metrics and the run command, with the gallery figure;
  • the forward model and its discretization, and the inverse-crime guard: how the data are simulated independently of the inversion operator;
  • the prior, the objective, the curriculum and the full configuration;
  • measured results — validation against analytic cases, smoke and paper-scale runs, baselines — and the known limitations, where they have been measured.