Datasetpublic

OpenScientificCodeRegistry/Database

Open Scientific Code Registry (OSCR): the authors' scripts The code published by the authors of open-access neuroscience papers, as found and verified by Open Scientific Code Registry (OSCR). Each file is here exactly as it is at the source, at the verified commit, under the license of its repository. 421,275 unique files (3,782 MB of text) from 8,849 repositories, in 24 Parquet block(s). Only files whose repository's license allows redistribution, confirmed by the repository's… See the full description on the dataset page: https://huggingface.co/datasets/OpenScientificCodeRegistry/Database.

sourceHugging Faceotherupdated 2d agoView on Hugging Face

0likes5.6kdownloads

rootmanifestse8github.com__dyballa__neuralencodingmanifolds.json

github.com__dyballa__neuralencodingmanifolds.json264 linesDownload Raw Back to e8

1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/dyballa/neuralencodingmanifolds",4 "url": "https://github.com/dyballa/NeuralEncodingManifolds",5 "host": "github.com",6 "commit": "ddccf17c8dc1e3d129624c05285dd5ec24a97e41",7 "license": "BSD-2-Clause",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11  {12   "path": "CNNs/build-CNN-manifold-resnet50_block3.ipynb",13   "sha256": "f1e04dcd3f5c83d49745fa9d7c7dab7506f51a6d3ae38b717bbb0d2f41b40709",14   "language": "Jupyter",15   "lines": 822,16   "truncated": false,17   "block": 1,18   "row": 203219  },20  {21   "path": "CNNs/classification-examples-ResNet50.ipynb",22   "sha256": "86c1854fae1206cde3e7226dbeadd235487b094dc9f17d03c2fc9a7d4286efaa",23   "language": "Jupyter",24   "lines": 72,25   "truncated": false,26   "block": 1,27   "row": 170128  },29  {30   "path": "CNNs/sampling-active-neurons.ipynb",31   "sha256": "d1e6f4b724a02bda5c01332b4eba4b7db4619df956364af5b2b7e0dc7b1ab2b6",32   "language": "Jupyter",33   "lines": 365,34   "truncated": false,35   "block": 1,36   "row": 193337  },38  {39   "path": "CNNs/test-set-activities-ResNet50.ipynb",40   "sha256": "01d1ef799aa07edbf750f2d329c8d7f45a2cb13a3a2ab9a8179d0badbee872c0",41   "language": "Jupyter",42   "lines": 263,43   "truncated": false,44   "block": 1,45   "row": 185846  },47  {48   "path": "CNNs/utils.py",49   "sha256": "a593014c47d83762b3a8a4cb1071e937327beab3f8c57745dcfc4af95a5a4936",50   "language": "Python",51   "lines": 289,52   "truncated": false,53   "block": 1,54   "row": 833755  },56  {57   "path": "LICENSE",58   "sha256": "3200f83804750dbf48d3680afbbe8db4048e44a66c451cd254f035d3129cbd5a",59   "language": "License",60   "lines": 24,61   "truncated": false,62   "block": 1,63   "row": 218664  },65  {66   "path": "README.md",67   "sha256": "d65cd52673a68c7eb76f194321d53a453a8c419ceb1a548abda4189e39536890",68   "language": "Text",69   "lines": 42,70   "truncated": false,71   "block": 1,72   "row": 1184573  },74  {75   "path": "allen-data-analysis/build-tensor-drifting-gratings.ipynb",76   "sha256": "03e2778b1f26ff38186d6225dee53fa35a08c9cafaeacb64fa6c67e116a6fc30",77   "language": "Jupyter",78   "lines": 328,79   "truncated": false,80   "block": 1,81   "row": 190982  },83  {84   "path": "allen-data-analysis/encoding-manifold-VISp.ipynb",85   "sha256": "0427c9d5c98ae6dbb8c0dc3cba352fa6771f850aa278f3805b694ffce9755056",86   "language": "Jupyter",87   "lines": 333,88   "truncated": false,89   "block": 1,90   "row": 193691  },92  {93   "path": "allen-data-analysis/filtering-natural-scenes/ffttools.py",94   "sha256": "5a7a57f11f2eb67bf7a7fb686818029b3e20c48b267ee144cb6b54aa8a1f9fc5",95   "language": "Python",96   "lines": 688,97   "truncated": false,98   "block": 1,99   "row": 9431100  },101  {102   "path": "allen-data-analysis/filtering-natural-scenes/filtering-natural-scenes.ipynb",103   "sha256": "930b8e0ac323c54d4f1233a105375f7a6bc4c304a72ab65e21ccea92118453b7",104   "language": "Jupyter",105   "lines": 199,106   "truncated": false,107   "block": 1,108   "row": 1850109  },110  {111   "path": "allen-data-analysis/load-factorization-VISp-dg.ipynb",112   "sha256": "9bff6d9fc14a849c537a5012401c26828494e8563d7def29b41282b00ac24381",113   "language": "Jupyter",114   "lines": 256,115   "truncated": false,116   "block": 1,117   "row": 1866118  },119  {120   "path": "allen-data-analysis/load-factorization-VISp-sg.ipynb",121   "sha256": "2d79d6bca825f5fc9f02ce37f8a209db0ac1f353fa1c2c355a45ffccc65d8bd6",122   "language": "Jupyter",123   "lines": 258,124   "truncated": false,125   "block": 1,126   "row": 1868127  },128  {129   "path": "allen-data-analysis/read_spike_data-drifting gratings.ipynb",130   "sha256": "6d3cf6a2a0032945656af9cf8edba13f7e17a688698bab41ee75b9de209105fd",131   "language": "Jupyter",132   "lines": 488,133   "truncated": false,134   "block": 1,135   "row": 1981136  },137  {138   "path": "allen-data-analysis/read_spike_data-natural_scenes.ipynb",139   "sha256": "05687d4b9b3384f281c4978c7c1548972908f3ff5b4d2446974b8990bc86c2ce",140   "language": "Jupyter",141   "lines": 528,142   "truncated": false,143   "block": 1,144   "row": 1985145  },146  {147   "path": "allen-data-analysis/read_spike_data-static-gratings.ipynb",148   "sha256": "e438e60fb27dbaf582a87ca8619d38e4ea4c5715942b67499b67f05aae5e0854",149   "language": "Jupyter",150   "lines": 696,151   "truncated": false,152   "block": 1,153   "row": 2020154  },155  {156   "path": "allen-data-analysis/waveform-classification.ipynb",157   "sha256": "319be7322ccb2549d4b40ae1877eb5d5f6214a7e5bc0d004c70c18742ca42809",158   "language": "Jupyter",159   "lines": 144,160   "truncated": false,161   "block": 1,162   "row": 1796163  },164  {165   "path": "creating-the-tensor/creating-the-tensor.ipynb",166   "sha256": "47b4ed3e9ec3afb5bc3e22dbc9fd5cd5a388507b13e88fd1986e9368b1456a4e",167   "language": "Jupyter",168   "lines": 302,169   "truncated": false,170   "block": 1,171   "row": 1893172  },173  {174   "path": "creating-the-tensor/utils.py",175   "sha256": "8898c259b9f227d9643c4c125e3f9b7efac3770834ae94d30bc3c491e787d8ae",176   "language": "Python",177   "lines": 223,178   "truncated": false,179   "block": 1,180   "row": 8159181  },182  {183   "path": "encoding-manifold/encoding-manifold.ipynb",184   "sha256": "2ea103a12fab0ac14d0146e2f40c82c6d25e7ac7d90831d4bef56415b29705c9",185   "language": "Jupyter",186   "lines": 289,187   "truncated": false,188   "block": 1,189   "row": 1919190  },191  {192   "path": "encoding-manifold/utils.py",193   "sha256": "981eaddc416db41be371956e32d783ee4cf03ba5dfeb25334d9c8bc69468564d",194   "language": "Python",195   "lines": 61,196   "truncated": false,197   "block": 1,198   "row": 6117199  },200  {201   "path": "permuted-decomposition/choosing-n-of-components.ipynb",202   "sha256": "8dac058f97ba0f792f54769678a7677b13d585fd678cd93a79e18b60b6964c19",203   "language": "Jupyter",204   "lines": 225,205   "truncated": false,206   "block": 1,207   "row": 1852208  },209  {210   "path": "permuted-decomposition/matlab/perm_cp_opt.m",211   "sha256": "be599b47e28005e8d321b6802860cd08ee66f7e512283967f87d5911bbab6f36",212   "language": "MATLAB",213   "lines": 220,214   "truncated": false,215   "block": 1,216   "row": 3854217  },218  {219   "path": "permuted-decomposition/matlab/perm_tt_cp_fg.m",220   "sha256": "bab315f1b2421a97e41500417f5f34a4ab7045aefb00b4053786e65a3ceaa259",221   "language": "MATLAB",222   "lines": 164,223   "truncated": false,224   "block": 1,225   "row": 3623226  },227  {228   "path": "permuted-decomposition/matlab/perm_tt_cp_fun.m",229   "sha256": "92d2d93818f2d452ee673bc608cf12b272d35493c233e5cf8c6e923cdff2b7b4",230   "language": "MATLAB",231   "lines": 62,232   "truncated": false,233   "block": 1,234   "row": 3210235  },236  {237   "path": "permuted-decomposition/matlab/run_permcp.m",238   "sha256": "76060c3c9d4813ea5c97b6b41d945bb11f9c3a3de6184f3d2fb377d019392ea9",239   "language": "MATLAB",240   "lines": 106,241   "truncated": false,242   "block": 1,243   "row": 3458244  },245  {246   "path": "permuted-decomposition/plotting-components.ipynb",247   "sha256": "f72a9d8c2150265e7a35700c681f6154f6892ad95f0862004741723bd1cfaba5",248   "language": "Jupyter",249   "lines": 123,250   "truncated": false,251   "block": 1,252   "row": 1753253  },254  {255   "path": "permuted-decomposition/utils.py",256   "sha256": "981eaddc416db41be371956e32d783ee4cf03ba5dfeb25334d9c8bc69468564d",257   "language": "Python",258   "lines": 61,259   "truncated": false,260   "block": 1,261   "row": 6117262  }263 ]264}