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File Type: Data

3,521 to 3,530 of 3,604 Results

T_Recon3D_301_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 302.8 MB - SHA-256: 9beb5d9968cb4f88c3c3fb2fe222f50ac9450e4be4063dad883b77fce32523fb
T_simplex_1024D_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 6.9 MB - SHA-256: b0df89ed2811ea17a75b65ce0e47dba2bd5d275050f845823a97b50fbb04a150
T_simplex_2048D_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 27.8 MB - SHA-256: 72da3eb445ce993094dcc4bbb49c14af6c69661c4187ddb41d330270d6953c75
T_simplex_256D_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 445.5 KB - SHA-256: 331969ca8c38cd8c90e2f92964b6ceb2df030d6aaf0a3afb9241a91fb6ae13ef
T_simplex_512D_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 1.7 MB - SHA-256: 885b291fd2a8bf3f3dd4d3d6dbaae427fd291c9ac6e5c77406b98fa73a7f9037
T_simplex_64D_rounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 27.9 KB - SHA-256: 2a76a1b04447cd12241100be6ee6c92ec9d793fafd6056ea12afabb6cee0e159
T_simplex_64D_unrounded.csv Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Comma Separated Values - 8.0 KB - SHA-256: 3a05d31942c6dcf688b614bc566f9efe5b20caa8a5a7c385efc3f37d69bdff1b
dataset_description.json Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects JSON - 276 B - SHA-256: 82bd306403e458773991dc62f3f540d08be4daeeb75cb771517160255a12486e
participants.json Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects JSON - 504 B - SHA-256: 9d13cf31db6d0618ced9cbb28f58fd20b582a34c257060b01988c37a932a4160
participants.tsv Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects Tab-Separated Values - 782 B - SHA-256: fc49ab8c967aea546651f18b0fd19e6f81a7ce345a36425209a1e31cd39b16b6

T_Recon3D_301_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 302.8 MB - SHA-256: 9beb5d9968cb4f88c3c3fb2fe222f50ac9450e4be4063dad883b77fce32523fb

T_simplex_1024D_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 6.9 MB - SHA-256: b0df89ed2811ea17a75b65ce0e47dba2bd5d275050f845823a97b50fbb04a150

T_simplex_2048D_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 27.8 MB - SHA-256: 72da3eb445ce993094dcc4bbb49c14af6c69661c4187ddb41d330270d6953c75

T_simplex_256D_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 445.5 KB - SHA-256: 331969ca8c38cd8c90e2f92964b6ceb2df030d6aaf0a3afb9241a91fb6ae13ef

T_simplex_512D_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 1.7 MB - SHA-256: 885b291fd2a8bf3f3dd4d3d6dbaae427fd291c9ac6e5c77406b98fa73a7f9037

T_simplex_64D_rounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 27.9 KB - SHA-256: 2a76a1b04447cd12241100be6ee6c92ec9d793fafd6056ea12afabb6cee0e159

T_simplex_64D_unrounded.csv

Dec 18, 2020 - Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Comma Separated Values - 8.0 KB - SHA-256: 3a05d31942c6dcf688b614bc566f9efe5b20caa8a5a7c385efc3f37d69bdff1b

dataset_description.json

Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

JSON - 276 B - SHA-256: 82bd306403e458773991dc62f3f540d08be4daeeb75cb771517160255a12486e

participants.json

Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

JSON - 504 B - SHA-256: 9d13cf31db6d0618ced9cbb28f58fd20b582a34c257060b01988c37a932a4160

participants.tsv

Dec 9, 2020 - Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

Tab-Separated Values - 782 B - SHA-256: fc49ab8c967aea546651f18b0fd19e6f81a7ce345a36425209a1e31cd39b16b6

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