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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Marques2020_Ringach2002-circular_variance")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	yudixie_resnet50_rotation_reg_0_240908	.984
2	cvt_cvt-13-224-in1k_4_LucyV4	.982
3	resnet-18-LC_1st_conv_m	.975
4	BiT-S-R50x1	.973
5	convnext_femto_ols:d1_in1k	.973
6	cvt_cvt-21-224-in1k_4_LucyV4	.971
7	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.969
8	yudixie_resnet18_translation_reg_0_240719	.966
9	resnet50_vicreg_linhead	.965
10	ReAlnet01_cornet_fov4	.962
11	BiT-M-R50x3	.961
12	xception	.962
13	yudixie_resnet50_distance_translation_rotation_0_240908	.958
14	yudixie_resnet50_category_class_0_240908	.958
15	compact_vgg19_V4	.958
16	compact_cornets_IT	.957
17	resnet50_barlowtwins_linhead	.956
18	yudixie_resnet18_category_class_0_240719	.955
19	mehrer2020_alexnet_training_seed_01_fov4	.952
20	mobilenet_v2_1.0_224-tf	.951
21	resnet50_byol_linhead	.952
22	resnet-152_v2-tf	.949
23	compact_resnet50_V4	.949
24	yudixie_resnet18_translation_rotation_0_240719	.946
25	efficientnet_b1_imagenet_full	.947
26	resnet-18-LC_d_w_sh_1x1_conv_init_m	.946
27	texture_shape_alexnet_trained_on_SIN	.944
28	convnext_large:fb_in22k_ft_in1k	.942
29	vgg_16	.942
30	resnet50_imagenet_100_seed-0	.942
31	briaai_rmbg_1_4	.941
32	inception_v1	.938
33	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.936
34	yudixie_resnet50_translation_rotation_0_240908	.935
35	efficientnet-b7	.935
36	alexnet_random_l2_3_perturb	.934
37	resnet50_simsiam_linhead	.934
38	mehrer2020_alexnet_training_seed_01_fov12	.934
39	AdvProp_efficientnet-b6	.930
40	mehrer2020_alexnet_training_seed_10	.930
41	vgg_19	.929
42	yudixie_resnet50_distance_rotation_0_240908	.925
43	yudixie_resnet50_distance_reg_0_240908	.924
44	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
45	0.5x_resnet-18_LC	.923
46	resnet-18-LC_m	.922
47	alexnet_random_linf8_perturb	.921
48	grcnn_robust_v1	.921
49	resnet-18-LC_w_sh_1_iter_m	.919
50	resnet50_primary_visual_cortex	.919
51	mehrer2020_alexnet_training_seed_01_fov16	.917
52	resnet18_ecoset_full	.918
53	cvt_cvt-21-384-in1k_4_LucyV4	.917
54	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
55	AdvProp_efficientnet-b8	.915
56	vgg-16-keras	.916
57	yudixie_resnet50_distance_translation_0_240908	.912
58	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
59	inception_v3-tf	.912
60	mehrer2020_alexnet_training_seed_01	.911
61	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
62	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
63	compact_cornets_V4	.909
64	resnet-50_v1-tf	.909
65	mehrer2020_alexnet_training_seed_03	.908
66	grcnn	.908
67	mehrer2020_alexnet_training_seed_04	.907
68	mobilenet_v2_1.0_96	.906
69	blt_vs	.907
70	deepeisnn_ei_cifar10_vgg19	.906
71	alexnet_robust_correct	.905
72	resnext101_32x32d_wsl	.904
73	resnext101_32x8d_wsl	.903
74	resnet18_fair	.902
75	grcnn_109	.902
76	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
77	resnet50_hvs_wzc	.901
78	BiT-S-R50x3	.897
79	alexnet_early_checkpoint	.899
80	mehrer2020_alexnet_training_seed_08	.898
81	grcnn_v2_text_noise	.898
82	BiT-S-R101x3	.895
83	nasnet_large-tf	.896
84	compact_resnet50_IT	.895
85	resnet18_imagenet21kP	.896
86	densenet-201-keras	.893
87	mobilenet_v2_1.3_224-tf	.893
88	mobilenet_v2_1.0_160-tf	.892
89	yudixie_resnet50_translation_reg_0_240908	.892
90	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.892
91	convnext_base_fb_in22k_ft_in1k	.891
92	resnet50_byol	.892
93	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
94	0.5x_resnet-18_LC_w_sh_10_iter	.890
95	yudixie_resnet50_object_class_0_240908	.889
96	alexnet_reduced_aliasing_early_checkpoint	.889
97	resnet50_ewconplus_wzc	.889
98	mobilenet_v2_0_75_192	.887
99	resnet50_imagenet_10_seed-0	.884
100	convnext_tiny_sup	.885
101	AdvProp_efficientnet-b7	.884
102	compact_resnet50_robust_V4	.883
103	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
104	alexnet_l2_3_robust	.882
105	ReAlnet01_cornet_fov16	.882
106	yudixie_resnet18_distance_rotation_0_240719	.882
107	yudixie_wbh_object_class_scaling_0415_run_3	.881
108	yudixie_wbh_object_class_scaling_0415_run_0	.881
109	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
110	compact_resnet50_robust_IT	.879
111	resnet101	.878
112	yudixie_resnet18_object_class_0_240719	.878
113	AlexNet_SIN_fov4	.877
114	squeezenet1_1	.877
115	densenet-201	.876
116	resnet50_st_wzc_seed6_2_323	.875
117	mobilenet_v1_1.0_128	.875
118	convnext_large_clip_laion2b_finelayers	.876
119	focalnet_tiny_lrf_in1k	.875
120	alexnet_linf_8_robust	.873
121	efficientnet_b0	.874
122	antialias-resnet152	.873
123	resnet_50_v2	.872
124	ReAlnet02	.872
125	ReAlnet02_cornet	.871
126	yudixie_resnet18_distance_translation_0_240719	.871
127	ReAlnet04	.871
128	ReAlnet03	.870
129	ReAlnet03_cornet	.867
130	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
131	ReAlnet04_cornet	.868
132	alexnet	.865
133	yudixie_resnet18_distance_translation_rotation_0_240719	.864
134	0.5x_resnet-18_LC_w_sh_100_iter	.865
135	inception_v3	.863
136	AlexNet_SIN	.863
137	resnet50-vitoimagevidnet8	.863
138	ReAlnet05	.863
139	ReAlnet05_cornet	.862
140	convnext_xlarge:fb_in22k_ft_in1k	.862
141	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
142	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
143	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
144	yudixie_wbh_object_class_scaling_0415_run_1	.861
145	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
146	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
147	omnivore_swinS	.862
148	resnet50-simclr-vissl	.861
149	ReAlnet01	.861
150	squeezenet1_0	.859
151	mehrer2020_alexnet_training_seed_09	.858
152	alexnet_fov16	.858
153	ReAlnet01_cornet	.858
154	AdvProp_efficientnet-b4	.858
155	convnext_xxlarge_clip	.858
156	mobilenet_v2_0_5_224	.858
157	mobilenet_v1_0.5_128	.857
158	ReAlnet08	.857
159	ReAlnet08_cornet	.857
160	ReAlnet07_cornet	.857
161	ReAlnet07	.857
162	resnet_50_v1_spiking_l4a	.855
163	ReAlnet09	.856
164	resnet_50_v1	.856
165	resnet_50_v1_spiking_l4	.856
166	resnet50-sup	.856
167	yudixie_resnet50_imagenet1kpret_0_240908	.855
168	ReAlnet09_cornet	.855
169	resnet50_tutorial	.855
170	resnet_50_v1_spiking_l3	.854
171	imagenet_l2_3_0	.855
172	ReAlnet10_cornet	.854
173	resnet_50_v1_spiking	.854
174	resnet50_st_wzc_seed7_2_323	.854
175	resnet50_ewconplus_wzc_seed5_2__323	.852
176	resnet50_ewconplus_wzc_seed2_2__323	.853
177	ReAlnet10	.852
178	alexnet_fov4	.852
179	resnet50-moclr8deg	.850
180	resnet50-vicregl0p9	.850
181	ViT_L_32_imagenet1k	.849
182	convnext_base_imagenet_full_seed-0	.848
183	convnext_tiny_imagenet_full_seed-0	.847
184	mobilenet_v2_1_0_128	.847
185	yudixie_wbh_object_class_scaling_0415_run_2	.845
186	ReAlnet06_cornet	.845
187	ReAlnet06	.845
188	mobilenet_v2_0.35_192	.843
189	inception_v4-tf	.843
190	convnext_base_fb_in1k	.842
191	inception_v2-tf	.843
192	convnext_large_in22k_supervised	.842
193	CLIP-RN50	.840
194	vonegrcnn_62e_nobn	.840
195	resnet50_random_linf8_perturb	.838
196	resnet-50-robust	.838
197	resnet50_robust_l2_eps1	.837
198	0.5x_resnet-18	.836
199	mobilenet_v1_0.5_160	.835
200	resnet50-vicregl0p75	.835
201	BiT-M-R101x1	.835
202	convnext_small_imagenet_100_seed-0	.835
203	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
204	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
205	resnet_SIN_IN_FT_IN	.832
206	mobilenet_v2_1_3_224	.832
207	mobilenet_v2_0.75_192-tf	.830
208	mobilenet_v2_1_4_224	.831
209	imagenet_l2_10_0	.831
210	resnet-18-LC_w_sh_10_iter_m	.830
211	Res2Net50_26w_4s	.830
212	CORnet-Z	.828
213	resnet101_imagenet_full	.826
214	omnivore_swinB	.825
215	resnet50_l2_3_robust	.825
216	resnext101_32x48d_wsl	.823
217	resnext101_32x16d_wsl	.824
218	resnet50	.822
219	antialiased-r50	.820
220	resnet18-supervised	.819
221	vgg-19-keras	.818
222	convnext_large_imagenet_full_seed-0	.818
223	alexnet_fov12	.818
224	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
225	resnet50_ewconplus_wzc_seed6_2_323	.817
226	resnet50_linf_8_robust	.817
227	AlexNet_SIN_fov12	.816
228	mobilenet_v2_0.5_96	.814
229	0.5x_resnet-18_LC_w_sh_1_iter	.813
230	resnet50-SIN_IN	.814
231	vit_base_patch16_clip_224:openai_ft_in1k	.813
232	resnet50-SIN_IN_IN	.813
233	resnet50_robust_l2_eps3	.812
234	resnet50_st_wzc_2	.813
235	mobilenet_v2_1.4_224-tf	.811
236	RN50	.812
237	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
238	resnet50_random_l2_perturb	.810
239	cornet_s	.808
240	CORnet-S	.806
241	vonealexnet_gaussian_noise_std4_fixed	.806
242	eicircuit_resnet18_bn_20260919	.806
243	BiT-S-R152x2	.803
244	ReAlnet07_ALL	.802
245	resnet50_linf_4_robust	.800
246	ReAlnet08_ALL	.800
247	densenet-169	.799
248	ReAlnet04_ALL	.798
249	convnext_small_imagenet_full_seed-0	.797
250	resnet50_st_wzc_seed3_2_323	.796
251	deepeisnn_ei_imagenet_resnet18	.796
252	resnet-50x2_untrained	.797
253	AdvProp_efficientnet-b0	.796
254	ReAlnet06_ALL	.793
255	resnet50-SIN	.792
256	ReAlnet03_ALL	.792
257	ReAlnet02_ALL	.791
258	resnet-50_untrained	.791
259	ReAlnet10_ALL	.791
260	texture_shape_resnet50_trained_on_SIN	.791
261	resnet-101_v2-tf	.790
262	ReAlnet05_ALL	.789
263	ReAlnet01_ALL	.788
264	ReAlnet01_cornet_fov12	.787
265	resnet-18_untrained	.788
266	CLIP_resnet50_float32	.788
267	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
268	r3m_resnet34_nocrop	.787
269	CLIP_resnet50	.785
270	resnet-50_v2-tf	.786
271	compact_vgg19_IT	.786
272	ReAlnet09_ALL	.785
273	resnet34_imagenet_full	.777
274	yudixie_resnet18_imagenet1kpret_0_240719	.777
275	yudixie_wbh_object_class_scaling_0415_imagenet	.774
276	SWSL_resnet50	.773
277	resnet50-vicreg	.773
278	resnet-101_v1-tf	.771
279	mobilenet_v2_0.35_96	.769
280	resnet-18_test_m	.766
281	densenet-121	.765
282	convnext_tiny:in12k_ft_in1k	.763
283	dinov2_vitl14_lc_res336	.762
284	resnet152_imagenet_full	.761
285	resnet50_imagenet_full	.760
286	alexnet_training_seed_01_fov16	.760
287	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
288	voneresnet-50-non_stochastic	.759
289	resnet18_imagenet_full	.758
290	deit_small_imagenet_full_seed-0	.757
291	pnasnet_large-tf	.757
292	pnasnet_large_halfPrecision	.757
293	efficientnet_b0_imagenet_full	.756
294	mobilenet_v2_1.0_192-tf	.754
295	mobilenet_v2_1_0_192	.754
296	resnet34_ecoset_full	.754
297	resnet101_ecoset_full	.749
298	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
299	resnet-152_v1-tf	.745
300	mobilenet_v1_0.5_224	.744
301	alexnet_training_seed_01_fov12	.744
302	alexnet_training_seed_07	.743
303	yudixie_resnet18_distance_reg_0_240719	.742
304	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
305	mobilenet_v1_0.75_192	.739
306	shufflenet_v2_x1_0	.740
307	cvt_cvt-13-384-in1k_4_LucyV4	.739
308	mobilenet_v2_0_75_224	.738
309	BiT-S-R101x1	.736
310	BiT-M-R101x3	.732
311	AlexNet_SIN_fov16	.732
312	alexnet_training_seed_02	.730
313	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
314	FrankRobWobv0	.727
315	voneresnet-50-robust	.727
316	vggface	.727
317	mobilenet_v2_0.5_192-tf	.726
318	yudixie_resnet18_rotation_reg_0_240719	.725
319	resnet50-cifar	.722
320	BiT-M-R152x4	.721
321	ijepa_vith14_linhead	.720
322	antialiased-rnext101_32x8d	.717
323	BiT-S-R152x4	.716
324	vit_base_patch14_reg4_dinov2-lvd142m	.716
325	resnet50-VITO-8deg-cc	.715
326	voneresnet-50	.714
327	resnet152_ecoset_full	.709
328	mobilenet_v1_0.25_224	.709
329	VOneCORnet-S	.708
330	yolos_tiny	.707
331	regnety_032	.704
332	densenet-121-keras	.703
333	resnet50_FractalDB	.703
334	mobilenet_v1_0.75_224	.701
335	vit_huge_clip336_laion	.702
336	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
337	alexnet_training_seed_04	.700
338	mobilenet_v2_0.75_128	.700
339	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
340	mobilenet_v1_0.25_160	.696
341	SWSL_resnext101_32x8d	.695
342	v1-pyr-nodown	.695
343	resnet-18-LC_w_sh_100_iter_m	.694
344	CLIP_ViT-B_32	.693
345	alexnet_training_seed_01	.693
346	deepeisnn_ei_cifar10_resnet18	.692
347	mobilenet_v1_1.0_224	.691
348	resnet50_ecoset_full	.691
349	omnivore_swinT	.690
350	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
351	densenet-169-keras	.687
352	my-model	.687
353	konkle_alexnetgn_ipcl_ref01_primary_model	.686
354	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
355	mobilenet_v2_1-4_224_pytorch	.684
356	alexnet_training_seed_09	.682
357	nasnet_mobile-tf	.681
358	mobilenet_v2_0.35_224	.680
359	mobilenet_v2_0_75_160	.680
360	effnetv2m_custom384	.676
361	eBarlow_lmda_02_1000ep	.676
362	resnet50-barlow	.675
363	mobilenet_v2_1.0_128-tf	.674
364	vision_transformer_vit_large_patch16_224	.670
365	mobilenet_v1_0.25_128	.668
366	convnext_base_fb_in1k_gram_aligned_dinov3	.667
367	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
368	vit_base_patch14_dinov2-lvd142m	.666
369	mobilenet_v2_1_0_160	.667
370	cv_18_dagger_408_pretrained	.665
371	dinov2_vitg14_reg_lc	.663
372	deit_small_imagenet_100_seed-0	.662
373	seresnext50_32x4d	.662
374	mobilenet_v1_0.5_192	.660
375	deit3_base_patch16_224_fb_in22k_ft_in1k	.661
376	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.660
377	resnet50_moco_v2	.658
378	resnet50_simclr	.657
379	custom_model_cv_18_dagger_408	.656
380	artResNet18_1	.655
381	nasnet_mobile	.654
382	eva02_large_in22k	.654
383	mobilenet_v2_1_0_224	.649
384	mobilenet_v1_1.0_192	.648
385	dinov2_vitl14_reg_lc_featread	.647
386	dinov2_vitl14_reg_lc	.647
387	yudixie_resnet50_random_0_240908	.646
388	effnetb1_272x240	.645
389	resnet-18-LC_conv_init_m	.644
390	alexnet_training_seed_10	.645
391	BiT-M-R152x2	.641
392	vit_large_clip336_openai	.635
393	AdvProp_efficientnet-b2	.627
394	mobilenet_v2_0.75_160-tf	.624
395	AT_efficientnet-b2	.625
396	vonegrcnn_52e_full	.623
397	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
398	vit_large_patch14_clip_224:openai_ft_in1k	.621
399	mobilenet_v2_0_5_192	.619
400	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
401	resnet-152_v2_pytorch	.615
402	convnext_small_imagenet_10_seed-0	.615
403	dinov2_vitl14_lc	.614
404	BiT-M-R50x1	.613
405	yudixie_resnet18_random_0_240719	.610
406	CORnetZ_CIFAR10_bs32_20_04	.605
407	vonegrcnn_47e	.604
408	inception_v1-tf	.600
409	mobilenet_v2_0.5_224-tf	.597
410	mobilenet_v1_1.0_160	.597
411	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.597
412	deit3_base_patch16_224_fb_in1k	.597
413	alexnet_training_seed_03	.596
414	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
415	deit_base_imagenet_full_seed-0	.589
416	r3m_resnet34	.590
417	vonegrcnn_47e	.581
418	deit_large_imagenet_full_seed-0	.577
419	mobilenet_v1_0.75_128	.570
420	mobilenet_v1_0.75_160	.565
421	mobilenet_v1_0.25_192	.560
422	mobilenet_v2_0.75_96	.557
423	inception_resnet_v2	.554
424	alexnet_training_seed_01_fov4	.554
425	efficientnet_b2_imagenet_full	.550
426	r3m_resnet50_nocrop	.550
427	hmax	.535
428	r3m_resnet50	.519
429	r3m_resnet18	.516
430	resnet50_pretrained_with_retinal_waves	.515
431	gabor_filter_mean_abs_4x4_v2	.496
432	my-model	.493
433	gabor_filter_entropy_4x4_v2_forcedCosine	.492
434	mobilenet_v2_0.75_224-tf	.490
435	alexnet_training_seed_08	.462
436	convnext_small_imagenet_1_seed-0	.459
437	CORnetZ_CIFAR10	.447
438	vit_base_patch16_dinov3-lvd1689m	.445
439	ViT-B/32	.385
440	mobilenet_v2_0.35_128	.375
441	deit_small_imagenet_10_seed-0	.375
442	resnet50_imagenet_1_seed-0	.355
443	alexnet_training_seed_05	.271
444	mobilenet_v2_0.5_160	.271
445	alexnet_training_seed_06	.215
446	resnet-18-LC_untrained	.170
447	gabor_filter_entropy_4x4	.028
448	gabor_filter_entropy_4x4_v2	.028
449	mobilenet_v2_0.5_128	.028
450	unet_entire
451	mobilenet_v2_0.35_160
452	fitvid_trained_on_physion
453	openclip
454	resnet50_ImageNet
455	resnet_101_v1
456	resnet_152_v2
457	regnet_y_400mf
458	tv_efficientnet-b1
459	alexnet_ks_torevert
460	yudixie_resnet50_imagenet1kpret_0_240312
461	resnet_152_v1
462	densenet_201_pytorch
463	inception_v3_pytorch
464	pnasnet_large_pytorch
465	mobilevit_small
466	inception_v4
467	nasnet_large
468	deit_small_imagenet_1_seed-0
469	pnasnet_large
470	vonegrcnn_62e_nobn
471	resnet_101_v2
472	vonegrcnn_52e_full
473	resnet50_simclr_linhead_01norm
474	mehrer2020_alexnet_training_seed_02
475	mehrer2020_alexnet_training_seed_05
476	mehrer2020_alexnet_training_seed_06
477	mehrer2020_alexnet_training_seed_07
478	pr1_stl10_disentangled_alpha04
479	predictive_coding_pc
480	dinov2_vitg14_lc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance