Datasets:
Formats:
csv
Languages:
English
Size:
< 1K
Tags:
continual-learning
catastrophic-forgetting
functional-memory
orthogonal-projection
statistical-certification
pytorch
| dataset,method,n_seeds,accuracy_mean,accuracy_std,accuracy_t95_low,accuracy_t95_high,peak_persistent_payload_mean_bytes,protected_class_count_mean,fit_mean_seconds,calibration_mean_seconds,inference_batch1_mean_seconds | |
| mnist,sgd,10,0.19312,0.014397206519167373,0.18282085888982777,0.20341914111017226,474045.0,0.0,1.218909727197024,0.0,5.1173799874959514e-05 | |
| mnist,er,10,0.8996500000000001,0.011557320912160702,0.8913823906709667,0.9079176093290334,6288307.0,0.0,2.6944549678984915,0.0,5.596409901045263e-05 | |
| mnist,derpp,10,0.92028,0.009765449298419403,0.9132942184044693,0.9272657815955306,6287872.0,0.0,4.050449650102382,0.0,5.068019963800907e-05 | |
| mnist,er_ace,10,0.9266900000000001,0.01622607298283981,0.9150825666349417,0.9382974333650586,6288249.0,0.0,2.9037213403986244,0.0,7.322919991565868e-05 | |
| mnist,er_ace_4epochs,10,0.9515500000000001,0.003804164384811287,0.9488286647358777,0.9542713352641226,6288261.0,0.0,5.959706500899483,0.0,7.221560008474626e-05 | |
| mnist,rff_ridge,10,0.8944300000000001,0.002959748487812976,0.8923127234793068,0.8965472765206933,5388937.0,0.0,2.5173849417049494,0.0,0.00012795930160791613 | |
| mnist,global_prototypes,10,0.9647600000000001,0.0012112436217009152,0.9638935285104034,0.9656264714895967,4032894.4,0.0,7.129596485196089,0.0,0.0049960949996602725 | |
| mnist,scalar_center,10,0.19932,0.00892248097037291,0.1929372416194519,0.2057027583805481,4153640.3,10.0,4.589560845098458,0.31280248639959607,0.0002486265999323223 | |
| mnist,center_no_controller,10,0.8117699999999999,0.014303771841332233,0.8015376980318741,0.8220023019681256,4682664.1,0.0,5.547428067199507,0.0,0.00027926879774895494 | |
| mnist,immutable_regions,10,0.36609,0.06796431171332985,0.3174712602563266,0.41470873974367345,1532211.4,2.6,9.606733977095427,0.21684566420226475,0.00047704790049465375 | |
| mnist,renewal_risk20,10,0.9272000000000002,0.07874465061196222,0.870869470376486,0.9835305296235145,6265608.7,9.6,7.084770360800758,0.3476801296019403,0.004367452400038019 | |
| mnist,renewal_risk10,10,0.46548,0.22556507215829708,0.3041204678857909,0.6268395321142091,6265556.6,4.6,7.0625850158008685,0.33937528699898395,0.00046068129959166983 | |
| mnist,joint_reference,10,0.93119,0.0039320478125272,0.9283771824427017,0.9340028175572982,43674061.0,0.0,3.8375634208023257,0.0,5.0837598246289416e-05 | |
| fashion_mnist,sgd,10,0.18983,0.03060748093014008,0.16793472714225888,0.21172527285774112,474045.0,0.0,1.1809794221997436,0.0,5.533210060093552e-05 | |
| fashion_mnist,er,10,0.78287,0.014276558097493647,0.7726571655714665,0.7930828344285334,6288307.0,0.0,2.7194814774993574,0.0,5.197890059207566e-05 | |
| fashion_mnist,derpp,10,0.78628,0.01867367725495496,0.7729216560158007,0.7996383439841993,6287872.0,0.0,4.133613903300284,0.0,5.451200049719773e-05 | |
| fashion_mnist,er_ace,10,0.8001199999999999,0.018216341869626597,0.78708881404204,0.8131511859579599,6288249.0,0.0,3.101824217201647,0.0,8.56841004861053e-05 | |
| fashion_mnist,er_ace_4epochs,10,0.8259699999999999,0.010461468985440495,0.8184863159146671,0.8334536840853326,6288261.0,0.0,5.873029302398936,0.0,8.45832000777591e-05 | |
| fashion_mnist,rff_ridge,10,0.80123,0.0020923405289026897,0.7997332297530071,0.8027267702469929,5388937.0,0.0,2.577795539102226,0.0,0.0001227053006005008 | |
| fashion_mnist,global_prototypes,10,0.8463499999999999,0.0017683953806267906,0.8450849661519819,0.847615033848018,4032892.5,0.0,7.092828380600986,0.0,0.00510300840032869 | |
| fashion_mnist,scalar_center,10,0.19455,0.009809547503438792,0.18753267244896776,0.20156732755103224,4153647.8,10.0,4.435896517702349,0.32063816609952484,0.0002723943020100705 | |
| fashion_mnist,center_no_controller,10,0.6618700000000001,0.021091180357886298,0.6467822784759133,0.6769577215240868,4682677.4,0.0,5.246229322200816,0.0,0.0002934800009825267 | |
| fashion_mnist,immutable_regions,10,0.29297000000000006,0.05721025646197056,0.25204424794757657,0.33389575205242356,1370700.9,2.2,9.105868710999493,0.2139103513014561,0.00043726320072892124 | |
| fashion_mnist,renewal_risk20,10,0.35503,0.21541921945618295,0.20092837368320937,0.5091316263167907,6265496.2,3.6,6.775431809399015,0.3504053646007378,0.0003829952998785302 | |
| fashion_mnist,renewal_risk10,10,0.17917999999999998,0.04177247365856558,0.14929777248886741,0.20906222751113254,6265444.1,1.6,6.825341928099806,0.34620971820113483,0.00020850229848292656 | |
| fashion_mnist,joint_reference,10,0.81145,0.019057704770278898,0.7978169392806309,0.8250830607193691,43674061.0,0.0,3.923530773001403,0.0,5.054700013715774e-05 | |