Exact-Jacobian Flow Controller / bench_report.json
Mechanism confirmed, baseline not beaten
1{
2 "bench_version": 1,
3 "track": "dynamics",
4 "model": "rnn_small",
5 "metric_direction": "lower is better",
6 "n_seeds": 8,
7 "baseline": {
8 "best_cfg": {
9 "lr": 0.01
10 },
11 "sweep": [
12 {
13 "cfg": {
14 "lr": 0.001
15 },
16 "mean": 0.010650048730894923
17 },
18 {
19 "cfg": {
20 "lr": 0.003
21 },
22 "mean": 0.0021922332525718957
23 },
24 {
25 "cfg": {
26 "lr": 0.01
27 },
28 "mean": 0.0001847558050940279
29 }
30 ],
31 "full": {
32 "mean": 0.00020586385835485999,
33 "std": 5.912498369648286e-05,
34 "per_seed": [
35 0.00017305620713159442,
36 0.00018997277948074043,
37 0.00013568498252425343,
38 0.0002403092512395233,
39 0.00026725101633928716,
40 0.00018888202612288296,
41 0.0003143867361359298,
42 0.00013736786786466837
43 ],
44 "n": 8
45 },
46 "idea_union_sweep": [
47 {
48 "cfg": {
49 "lr": 0.01,
50 "K": 4
51 },
52 "mean": 0.000600305080297403
53 },
54 {
55 "cfg": {
56 "lr": 0.001,
57 "K": 4
58 },
59 "mean": 0.0048645936767570674
60 },
61 {
62 "cfg": {
63 "lr": 0.01,
64 "K": 4
65 },
66 "mean": 0.000600305080297403
67 }
68 ]
69 },
70 "idea": {
71 "mean": 0.0005137363186804578,
72 "std": 0.00021520799203052408,
73 "per_seed": [
74 0.0005184079636819661,
75 0.00034054333809763193,
76 0.000662883510813117,
77 0.0008793855085968971,
78 0.00037677702493965626,
79 0.00013013248099014163,
80 0.0005593107198365033,
81 0.0006424500024877489
82 ],
83 "n": 8
84 },
85 "comparison": {
86 "delta_mean": 0.0003078724603255978,
87 "idea_wins": 1,
88 "n_pairs": 8,
89 "per_seed_diffs": [
90 0.00034535175655037165,
91 0.0001505705586168915,
92 0.0005271985282888636,
93 0.0006390762573573738,
94 0.0001095260086003691,
95 -5.874954513274133e-05,
96 0.00024492398370057344,
97 0.0005050821346230805
98 ],
99 "p_value": 0.0163,
100 "mde": 0.00020001775934380757,
101 "mde_rel_pct": 97.16021109398662,
102 "verdict": "idea worse (significant)",
103 "system_worked": false
104 },
105 "mechanism_signature": {
106 "prediction": "analytic triangular inverse and logdet remain exact after training",
107 "reconstruction_max_abs": 1.1920928955078125e-07,
108 "observed_mean_abs_logdet": 0.786198616027832,
109 "observed_jacobian_logdet_abs_error": 1.1920928955078125e-07,
110 "jacobian_sign": 1.0,
111 "confirmed": true
112 },
113 "protocol_notes": {
114 "epochs": 12,
115 "n_train": 800,
116 "n_test": 300,
117 "idea_configs": [
118 {
119 "lr": 0.01,
120 "K": 4
121 },
122 {
123 "lr": 0.001,
124 "K": 4
125 },
126 {
127 "lr": 0.01,
128 "K": 4
129 }
130 ],
131 "structural_match": "controlled pendulum multi-step rollout; flow is trained end-to-end with shared GRU encoder"
132 }
133}