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gaussian_kernel

Syntologyfunction-name censuscensus 2026-09-22battery b986f7e04d79all samples with this name

gaussian_kernel: 9 implementations from 9 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 9 distinct outputs across 6 buckets, one shared input per bucket.

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence. Implementations are compared only within one bucket, the positional (rank, kind, dtype) of each array argument; the argument name is not part of the key because the harness draws the shared array from (rank, kind) and casts it to the dtype, whatever the name; each bucket's shared input is fixed by that key, so members of one bucket saw bitwise-identical inputs under their own scalar arguments. A cluster is the set of members whose recorded output digest is identical. Nothing here says which computation a paper's method intended, and nothing reproduces a paper's results.

Not compared, and not in the tables or the counts above:

Bucket 1 of 6: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 2, kind float, dtype float32 · arg 3: rank 0, kind float, dtype float32

2 implementations from 2 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
26e83ea82d46

RAMEN/models/ramen.py 1c4221b5
recorded xi:2/float/float32, xj:2/float/float32, sigma:0/float/float32
[1, 0.00558354, 0.364905, 0.00567157, 0.00558354, 1, 0.00505368, 0.0284598, …]
shape [4, 4] · float32 · Tensor
1 implementation
1 paper
cce4610e8a21

SWAE/xp_swae.py dc6fed6b
recorded x:2/float/float32, y:2/float/float32, h:0/float/float32
[1, 2.60623e+06, 17.6505, 2.49269e+06, 2.60623e+06, 1, 3.46195e+06, 25223.7, …]
shape [4, 4] · float32 · Tensor

Bucket 2 of 6: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 2, kind float, dtype float32

2 implementations from 2 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
26c85e34ff6e

utils/kernels.py 447cd6e5
recorded samples_x:2/float/float32, samples_y:2/float/float32; h=-1, get_width=False, detach=False
[1, 0.0957616, 0.633907, 0.0964413, 0.0957616, 1, 0.09154, 0.2, …]
shape [4, 4] · float32 · Tensor
1 implementation
1 paper
60a04014ec19

Ablation/nn_bandwidth/Kernels.py 4bd0b303
recorded A:2/float/float32, B:2/float/float32; sigma=1.0
[1, 7.32352e-10, 0.0167817, 7.80305e-10, 7.32352e-10, 1, 4.88823e-10, 5.40251e-07, …]
shape [4, 4] · float32 · Tensor

Bucket 3 of 6: arg 1: rank 2, kind float, dtype float32

2 implementations from 2 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
34cc6a9f8535

overcomplete/sae/jump_sae.py cb509c06
recorded x:2/float/float32; bandwith=0.5
[4.09378e-12, 5.35332e-09, 0.130184, 0.0175204, 0.00117453, 0.000163163, 0.0237587, 0.057763, …]
shape [4, 8] · float32 · Tensor
1 implementation
1 paper
6236892e74fb

sispca/model.py 1f9ef962
recorded x:2/float/float32; bw=None
[1, 0.482491, 0.867952, 0.483552, 0.482491, 1, 0.47578, 0.606531, …]
shape [4, 4] · float32 · Tensor

Bucket 4 of 6: arg 1: rank 1, kind float, dtype float32 · arg 2: rank 0, kind float, dtype float32 · arg 3: rank 2, kind float, dtype float32

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
2f84fa4fd5d5

mta.py abf7adc7
recorded mu:1/float/float32, bandwidth:0/float/float32, datapoints:2/float/float32
[0.0352402, 0.0527988, 0.121716, 0.221164]
shape [4] · float32 · Tensor

Bucket 5 of 6: arg 1: rank 1, kind float, dtype float32

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
2c17218ed2d6

KMIFQE.py 375fe0e2
recorded u:1/float/float32
[5.41208e-05]
shape [] · float32 · Tensor

Bucket 6 of 6: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 0, kind float, dtype float32

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
26e83ea82d46

our_method/lisc_linear.py c345cceb
recorded z:2/float/float32, p:0/float/float32
[1, 0.00558353, 0.364905, 0.00567156, 0.00558353, 1, 0.00505368, 0.0284598, …]
shape [4, 4] · float32 · Tensor

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence; where a cluster's members carry recorded values, the largest difference among them is shown under the cluster. Paper titles are the archive's archive 2025-07-28 where the paper is in the archive and the graph's where it was added by Syntology; papers with no page here are shown by their recorded paper id only. A paper count above the implementation count means one implementation (one code sha) is held from several papers' repositories and counts once. Per-sample status, licence and fingerprint records for each paper are on its paper page. JSON twin: /census/gaussian-kernel.json.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections