Conditional Sinkhorn Adversarial Augmentation / results.json
Failed on benchmark
1{
2 "math_checks": {
3 "translation_scaling": {
4 "prediction": "S approximately k*delta^2",
5 "fitted_k": 0.9857734603617165,
6 "max_relative_error": 0.0027633349934145365,
7 "deltas": [
8 0.0,
9 0.19999999999999998,
10 0.39999999999999997,
11 0.6,
12 0.7999999999999999,
13 0.9999999999999999,
14 1.2
15 ],
16 "S": [
17 0.0,
18 0.039322277785479934,
19 0.15734388263442262,
20 0.35421841197822845,
21 0.6301666228773719,
22 0.985437594691379,
23 1.420280987318515
24 ]
25 },
26 "radius_boundary": {
27 "prediction": "boundary delta=sqrt(rho/k)",
28 "rho": 0.36,
29 "predicted_delta": 0.6043140473283364,
30 "observed_delta": 0.6,
31 "absolute_error": 0.004314047328336401
32 },
33 "debiased_identity": {
34 "prediction": "S(A,A)=0",
35 "observed": 0.0
36 },
37 "multiplier_projection": {
38 "prediction": "lambda increases only for violations",
39 "sequence": [
40 [
41 0.2,
42 0.03932227778547999,
43 0.0
44 ],
45 [
46 0.5,
47 0.24591182732893413,
48 0.0
49 ],
50 [
51 0.8,
52 0.6301666228773722,
53 0.2161332983018978
54 ],
55 [
56 1.0,
57 0.9854375946913786,
58 0.7164833740550007
59 ]
60 ]
61 }
62 },
63 "training": {
64 "ordinary": {
65 "clean_mse": 0.18821489138674305,
66 "shifted_mse": 0.47675823278697876,
67 "psi": NaN,
68 "final_sinkhorn": NaN,
69 "lambda": 0.0
70 },
71 "unconstrained": {
72 "clean_mse": 0.45381627742423153,
73 "shifted_mse": 0.19558308193952534,
74 "psi": NaN,
75 "final_sinkhorn": NaN,
76 "lambda": 0.0
77 },
78 "sinkhorn": {
79 "clean_mse": 0.18928426842945464,
80 "shifted_mse": 0.4955903092770569,
81 "psi": -0.5193771052360537,
82 "final_sinkhorn": 0.25516605377197266,
83 "lambda": 0.8380940005704756
84 }
85 }
86}