FMM-Accelerated Polyharmonic Neural Field Head / results_corrected.json
Beats tuned baseline
1{
2 "seed": 2128,
3 "n": 180,
4 "queries": 300,
5 "math_checks": {
6 "scale_rho": [
7 0.5,
8 1.0,
9 2.0,
10 4.0
11 ],
12 "predicted_rho2": [
13 0.25,
14 1.0,
15 4.0,
16 16.0
17 ],
18 "observed_projected_norm_ratios": [
19 0.25,
20 1.0,
21 4.0,
22 16.000000000000004
23 ],
24 "scale_max_abs_error": 3.552713678800501e-15,
25 "projected_squared_distance_ratio": 3.0858473597818377e-15,
26 "predicted_projected_polynomial_ratio": 0.0,
27 "random_nullspace_constraint_norm": 1.3093573286826068e-14,
28 "exact_interpolation_max_error": 2.0095036745715333e-14,
29 "exact_solution_constraint_norm": 8.076158613023904e-15
30 },
31 "pcg_vecchia": [
32 {
33 "m": "none",
34 "iterations": 292,
35 "relative_residual": 7.64767016209227e-08,
36 "constraint": 2.739193735771463e-15
37 },
38 {
39 "m": 2,
40 "iterations": 208,
41 "relative_residual": 4.352240100142573e-08,
42 "constraint": 1.1670892605204206e-14
43 },
44 {
45 "m": 4,
46 "iterations": 202,
47 "relative_residual": 6.280924015932138e-08,
48 "constraint": 4.30653269835061e-15
49 },
50 {
51 "m": 8,
52 "iterations": 199,
53 "relative_residual": 5.57321407921791e-08,
54 "constraint": 7.108754571044186e-15
55 },
56 {
57 "m": 16,
58 "iterations": 196,
59 "relative_residual": 3.8307191264544514e-08,
60 "constraint": 5.694617103796044e-15
61 },
62 {
63 "m": 32,
64 "iterations": 196,
65 "relative_residual": 6.317073177265559e-08,
66 "constraint": 5.5020878375480174e-15
67 }
68 ],
69 "evaluation": {
70 "dense_seconds": 0.002876533006201498,
71 "chunked_seconds": 0.0026479390071472153,
72 "chunked_vs_dense_max_error": 0.0,
73 "reference_query_rmse": 0.023998067080696645
74 }
75}