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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	ReAlnet01_cornet_fov4	.962
10	BiT-M-R50x3	.961
11	xception	.962
12	yudixie_resnet50_distance_translation_rotation_0_240908	.958
13	yudixie_resnet50_category_class_0_240908	.958
14	compact_vgg19_V4	.958
15	compact_cornets_IT	.957
16	yudixie_resnet18_category_class_0_240719	.955
17	mobilenet_v2_1.0_224-tf	.951
18	resnet-152_v2-tf	.949
19	compact_resnet50_V4	.949
20	yudixie_resnet18_translation_rotation_0_240719	.946
21	efficientnet_b1_imagenet_full	.947
22	resnet-18-LC_d_w_sh_1x1_conv_init_m	.946
23	texture_shape_alexnet_trained_on_SIN	.944
24	convnext_large:fb_in22k_ft_in1k	.942
25	vgg_16	.942
26	resnet50_imagenet_100_seed-0	.942
27	briaai_rmbg_1_4	.941
28	inception_v1	.938
29	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.936
30	yudixie_resnet50_translation_rotation_0_240908	.935
31	efficientnet-b7	.935
32	alexnet_random_l2_3_perturb	.934
33	AdvProp_efficientnet-b6	.930
34	vgg_19	.929
35	yudixie_resnet50_distance_rotation_0_240908	.925
36	yudixie_resnet50_distance_reg_0_240908	.924
37	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
38	0.5x_resnet-18_LC	.923
39	resnet-18-LC_m	.922
40	alexnet_random_linf8_perturb	.921
41	grcnn_robust_v1	.921
42	resnet-18-LC_w_sh_1_iter_m	.919
43	resnet50_primary_visual_cortex	.919
44	resnet18_ecoset_full	.918
45	cvt_cvt-21-384-in1k_4_LucyV4	.917
46	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
47	AdvProp_efficientnet-b8	.915
48	vgg-16-keras	.916
49	yudixie_resnet50_distance_translation_0_240908	.912
50	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
51	inception_v3-tf	.912
52	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
53	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
54	compact_cornets_V4	.909
55	resnet-50_v1-tf	.909
56	grcnn	.908
57	mobilenet_v2_1.0_96	.906
58	blt_vs	.907
59	deepeisnn_ei_cifar10_vgg19	.906
60	alexnet_robust_correct	.905
61	resnext101_32x8d_wsl	.903
62	resnet18_fair	.902
63	grcnn_109	.902
64	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
65	BiT-S-R50x3	.897
66	alexnet_early_checkpoint	.899
67	grcnn_v2_text_noise	.898
68	BiT-S-R101x3	.895
69	nasnet_large-tf	.896
70	compact_resnet50_IT	.895
71	resnet18_imagenet21kP	.896
72	densenet-201-keras	.893
73	mobilenet_v2_1.3_224-tf	.893
74	mobilenet_v2_1.0_160-tf	.892
75	yudixie_resnet50_translation_reg_0_240908	.892
76	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.892
77	convnext_base_fb_in22k_ft_in1k	.891
78	resnet50_byol	.892
79	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
80	0.5x_resnet-18_LC_w_sh_10_iter	.890
81	yudixie_resnet50_object_class_0_240908	.889
82	alexnet_reduced_aliasing_early_checkpoint	.889
83	resnet50_ewconplus_wzc	.889
84	mobilenet_v2_0_75_192	.887
85	resnet50_ewconplus_wzc_2_323	.886
86	resnet50_imagenet_10_seed-0	.884
87	convnext_tiny_sup	.885
88	AdvProp_efficientnet-b7	.884
89	compact_resnet50_robust_V4	.883
90	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
91	alexnet_l2_3_robust	.882
92	ReAlnet01_cornet_fov16	.882
93	yudixie_resnet18_distance_rotation_0_240719	.882
94	yudixie_wbh_object_class_scaling_0415_run_3	.881
95	yudixie_wbh_object_class_scaling_0415_run_0	.881
96	resnet50_ewconplus_wzc_seed4_2_323	.880
97	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
98	compact_resnet50_robust_IT	.879
99	resnet101	.878
100	yudixie_resnet18_object_class_0_240719	.878
101	AlexNet_SIN_fov4	.877
102	squeezenet1_1	.877
103	densenet-201	.876
104	resnet50_st_wzc_seed6_2_323	.875
105	mobilenet_v1_1.0_128	.875
106	focalnet_tiny_lrf_in1k	.875
107	alexnet_linf_8_robust	.873
108	efficientnet_b0	.874
109	antialias-resnet152	.873
110	resnet_50_v2	.872
111	ReAlnet02	.872
112	ReAlnet02_cornet	.871
113	yudixie_resnet18_distance_translation_0_240719	.871
114	ReAlnet04	.871
115	ReAlnet03	.870
116	resnet50_st_wzc_seed4_2_323	.869
117	ReAlnet03_cornet	.867
118	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
119	ReAlnet04_cornet	.868
120	alexnet	.865
121	yudixie_resnet18_distance_translation_rotation_0_240719	.864
122	0.5x_resnet-18_LC_w_sh_100_iter	.865
123	resnet50_st_wzc_seed5_2_323	.864
124	inception_v3	.863
125	AlexNet_SIN	.863
126	resnet50-vitoimagevidnet8	.863
127	ReAlnet05	.863
128	ReAlnet05_cornet	.862
129	convnext_xlarge:fb_in22k_ft_in1k	.862
130	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
131	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
132	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
133	yudixie_wbh_object_class_scaling_0415_run_1	.861
134	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
135	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
136	omnivore_swinS	.862
137	resnet50-simclr-vissl	.861
138	ReAlnet01	.861
139	squeezenet1_0	.859
140	alexnet_fov16	.858
141	ReAlnet01_cornet	.858
142	AdvProp_efficientnet-b4	.858
143	mobilenet_v2_0_5_224	.858
144	mobilenet_v1_0.5_128	.857
145	ReAlnet08	.857
146	ReAlnet08_cornet	.857
147	ReAlnet07_cornet	.857
148	ReAlnet07	.857
149	resnet_50_v1_spiking_l4a	.855
150	ReAlnet09	.856
151	resnet_50_v1	.856
152	resnet_50_v1_spiking_l4	.856
153	resnet50-sup	.856
154	yudixie_resnet50_imagenet1kpret_0_240908	.855
155	ReAlnet09_cornet	.855
156	resnet50_tutorial	.855
157	resnet_50_v1_spiking_l3	.854
158	imagenet_l2_3_0	.855
159	ReAlnet10_cornet	.854
160	resnet_50_v1_spiking	.854
161	resnet50_st_wzc_seed7_2_323	.854
162	resnet50_ewconplus_wzc_seed5_2__323	.852
163	resnet50_ewconplus_wzc_seed2_2__323	.853
164	ReAlnet10	.852
165	alexnet_fov4	.852
166	resnet50-moclr8deg	.850
167	resnet50-vicregl0p9	.850
168	resnet50_st_wzc_noseed_2_323	.850
169	convnext_base_imagenet_full_seed-0	.848
170	convnext_tiny_imagenet_full_seed-0	.847
171	mobilenet_v2_1_0_128	.847
172	yudixie_wbh_object_class_scaling_0415_run_2	.845
173	ReAlnet06_cornet	.845
174	ReAlnet06	.845
175	resnet50_st_wzc_2_323	.845
176	mobilenet_v2_0.35_192	.843
177	inception_v4-tf	.843
178	convnext_base_fb_in1k	.842
179	inception_v2-tf	.843
180	resnet50_ewconplus_wzc_seed7_2_323	.841
181	CLIP-RN50	.840
182	vonegrcnn_62e_nobn	.840
183	resnet50_ewconplus_wzc_seed3_2_323	.838
184	resnet50_random_linf8_perturb	.838
185	resnet-50-robust	.838
186	resnet50_robust_l2_eps1	.837
187	0.5x_resnet-18	.836
188	mobilenet_v1_0.5_160	.835
189	resnet50-vicregl0p75	.835
190	BiT-M-R101x1	.835
191	convnext_small_imagenet_100_seed-0	.835
192	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
193	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
194	resnet_SIN_IN_FT_IN	.832
195	mobilenet_v2_1_3_224	.832
196	mobilenet_v2_0.75_192-tf	.830
197	mobilenet_v2_1_4_224	.831
198	imagenet_l2_10_0	.831
199	resnet-18-LC_w_sh_10_iter_m	.830
200	Res2Net50_26w_4s	.830
201	CORnet-Z	.828
202	resnet101_imagenet_full	.826
203	omnivore_swinB	.825
204	resnet50_l2_3_robust	.825
205	resnet50	.822
206	antialiased-r50	.820
207	resnet50_ewconplus_noseed_2_323	.819
208	resnet18-supervised	.819
209	vgg-19-keras	.818
210	convnext_large_imagenet_full_seed-0	.818
211	alexnet_fov12	.818
212	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
213	resnet50_ewconplus_wzc_seed6_2_323	.817
214	resnet50_linf_8_robust	.817
215	AlexNet_SIN_fov12	.816
216	mobilenet_v2_0.5_96	.814
217	0.5x_resnet-18_LC_w_sh_1_iter	.813
218	resnet50-SIN_IN	.814
219	vit_base_patch16_clip_224:openai_ft_in1k	.813
220	resnet50-SIN_IN_IN	.813
221	resnet50_robust_l2_eps3	.812
222	resnet50_st_wzc_2	.813
223	mobilenet_v2_1.4_224-tf	.811
224	RN50	.812
225	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
226	resnet50_random_l2_perturb	.810
227	cornet_s	.808
228	CORnet-S	.806
229	vonealexnet_gaussian_noise_std4_fixed	.806
230	BiT-S-R152x2	.803
231	ReAlnet07_ALL	.802
232	aughost_fair_resnet18	.800
233	resnet50_linf_4_robust	.800
234	ReAlnet08_ALL	.800
235	densenet-169	.799
236	ReAlnet04_ALL	.798
237	convnext_small_imagenet_full_seed-0	.797
238	resnet50_st_wzc_seed3_2_323	.796
239	deepeisnn_ei_imagenet_resnet18	.796
240	resnet-50x2_untrained	.797
241	AdvProp_efficientnet-b0	.796
242	ReAlnet06_ALL	.793
243	resnet50-SIN	.792
244	ReAlnet03_ALL	.792
245	ReAlnet02_ALL	.791
246	resnet-50_untrained	.791
247	ReAlnet10_ALL	.791
248	texture_shape_resnet50_trained_on_SIN	.791
249	resnet-101_v2-tf	.790
250	ReAlnet05_ALL	.789
251	ReAlnet01_ALL	.788
252	ReAlnet01_cornet_fov12	.787
253	resnet-18_untrained	.788
254	CLIP_resnet50_float32	.788
255	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
256	r3m_resnet34_nocrop	.787
257	CLIP_resnet50	.785
258	resnet-50_v2-tf	.786
259	compact_vgg19_IT	.786
260	ReAlnet09_ALL	.785
261	resnet34_imagenet_full	.777
262	yudixie_resnet18_imagenet1kpret_0_240719	.777
263	yudixie_wbh_object_class_scaling_0415_imagenet	.774
264	SWSL_resnet50	.773
265	resnet50-vicreg	.773
266	resnet-101_v1-tf	.771
267	mobilenet_v2_0.35_96	.769
268	resnet-18_test_m	.766
269	densenet-121	.765
270	convnext_tiny:in12k_ft_in1k	.763
271	resnet152_imagenet_full	.761
272	resnet50_imagenet_full	.760
273	alexnet_training_seed_01_fov16	.760
274	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
275	voneresnet-50-non_stochastic	.759
276	resnet18_imagenet_full	.758
277	deit_small_imagenet_full_seed-0	.757
278	pnasnet_large-tf	.757
279	pnasnet_large_halfPrecision	.757
280	efficientnet_b0_imagenet_full	.756
281	mobilenet_v2_1.0_192-tf	.754
282	mobilenet_v2_1_0_192	.754
283	resnet34_ecoset_full	.754
284	resnet101_ecoset_full	.749
285	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
286	resnet-152_v1-tf	.745
287	mobilenet_v1_0.5_224	.744
288	alexnet_training_seed_01_fov12	.744
289	alexnet_training_seed_07	.743
290	yudixie_resnet18_distance_reg_0_240719	.742
291	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
292	mobilenet_v1_0.75_192	.739
293	shufflenet_v2_x1_0	.740
294	cvt_cvt-13-384-in1k_4_LucyV4	.739
295	mobilenet_v2_0_75_224	.738
296	BiT-S-R101x1	.736
297	BiT-M-R101x3	.732
298	AlexNet_SIN_fov16	.732
299	alexnet_training_seed_02	.730
300	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
301	FrankRobWobv0	.727
302	voneresnet-50-robust	.727
303	vggface	.727
304	mobilenet_v2_0.5_192-tf	.726
305	yudixie_resnet18_rotation_reg_0_240719	.725
306	resnet50-cifar	.722
307	BiT-M-R152x4	.721
308	antialiased-rnext101_32x8d	.717
309	BiT-S-R152x4	.716
310	vit_base_patch14_reg4_dinov2-lvd142m	.716
311	resnet50-VITO-8deg-cc	.715
312	voneresnet-50	.714
313	resnet152_ecoset_full	.709
314	mobilenet_v1_0.25_224	.709
315	VOneCORnet-S	.708
316	yolos_tiny	.707
317	densenet-121-keras	.703
318	resnet50_FractalDB	.703
319	mobilenet_v1_0.75_224	.701
320	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
321	alexnet_training_seed_04	.700
322	mobilenet_v2_0.75_128	.700
323	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
324	mobilenet_v1_0.25_160	.696
325	SWSL_resnext101_32x8d	.695
326	v1-pyr-nodown	.695
327	resnet-18-LC_w_sh_100_iter_m	.694
328	CLIP_ViT-B_32	.693
329	alexnet_training_seed_01	.693
330	deepeisnn_ei_cifar10_resnet18	.692
331	mobilenet_v1_1.0_224	.691
332	resnet50_ecoset_full	.691
333	omnivore_swinT	.690
334	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
335	densenet-169-keras	.687
336	my-model	.687
337	konkle_alexnetgn_ipcl_ref01_primary_model	.686
338	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
339	mobilenet_v2_1-4_224_pytorch	.684
340	alexnet_training_seed_09	.682
341	nasnet_mobile-tf	.681
342	mobilenet_v2_0.35_224	.680
343	mobilenet_v2_0_75_160	.680
344	effnetv2m_custom384	.676
345	eBarlow_lmda_02_1000ep	.676
346	resnet50-barlow	.675
347	mobilenet_v2_1.0_128-tf	.674
348	vision_transformer_vit_large_patch16_224	.670
349	mobilenet_v1_0.25_128	.668
350	convnext_base_fb_in1k_gram_aligned_dinov3	.667
351	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
352	vit_base_patch14_dinov2-lvd142m	.666
353	mobilenet_v2_1_0_160	.667
354	cv_18_dagger_408_pretrained	.665
355	deit_small_imagenet_100_seed-0	.662
356	mobilenet_v1_0.5_192	.660
357	deit3_base_patch16_224_fb_in22k_ft_in1k	.661
358	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.660
359	resnet50	.658
360	resnet50_moco_v2	.658
361	resnet50_simclr	.657
362	custom_model_cv_18_dagger_408	.656
363	artResNet18_1	.655
364	nasnet_mobile	.654
365	mobilenet_v2_1_0_224	.649
366	mobilenet_v1_1.0_192	.648
367	yudixie_resnet50_random_0_240908	.646
368	effnetb1_272x240	.645
369	resnet-18-LC_conv_init_m	.644
370	alexnet_training_seed_10	.645
371	BiT-M-R152x2	.641
372	AdvProp_efficientnet-b2	.627
373	mobilenet_v2_0.75_160-tf	.624
374	AT_efficientnet-b2	.625
375	vonegrcnn_52e_full	.623
376	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
377	vit_large_patch14_clip_224:openai_ft_in1k	.621
378	mobilenet_v2_0_5_192	.619
379	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
380	resnet-152_v2_pytorch	.615
381	convnext_small_imagenet_10_seed-0	.615
382	BiT-M-R50x1	.613
383	yudixie_resnet18_random_0_240719	.610
384	CORnetZ_CIFAR10_bs32_20_04	.605
385	vonegrcnn_47e	.604
386	inception_v1-tf	.600
387	mobilenet_v2_0.5_224-tf	.597
388	mobilenet_v1_1.0_160	.597
389	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.597
390	deit3_base_patch16_224_fb_in1k	.597
391	alexnet_training_seed_03	.596
392	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
393	deit_base_imagenet_full_seed-0	.589
394	r3m_resnet34	.590
395	vonegrcnn_47e	.581
396	deit_large_imagenet_full_seed-0	.577
397	mobilenet_v1_0.75_128	.570
398	mobilenet_v1_0.75_160	.565
399	mobilenet_v1_0.25_192	.560
400	mobilenet_v2_0.75_96	.557
401	inception_resnet_v2	.554
402	alexnet_training_seed_01_fov4	.554
403	efficientnet_b2_imagenet_full	.550
404	r3m_resnet50_nocrop	.550
405	hmax	.535
406	r3m_resnet50	.519
407	r3m_resnet18	.516
408	resnet50_pretrained_with_retinal_waves	.515
409	my-model	.493
410	mobilenet_v2_0.75_224-tf	.490
411	alexnet_training_seed_08	.462
412	convnext_small_imagenet_1_seed-0	.459
413	CORnetZ_CIFAR10	.447
414	vit_base_patch16_dinov3-lvd1689m	.445
415	ViT-B/32	.385
416	mobilenet_v2_0.35_128	.375
417	deit_small_imagenet_10_seed-0	.375
418	resnet50_imagenet_1_seed-0	.355
419	alexnet_training_seed_05	.271
420	mobilenet_v2_0.5_160	.271
421	alexnet_training_seed_06	.215
422	resnet-18-LC_untrained	.170
423	resnet50-meshes-lt-100-original-pretrained	.169
424	resnet50-meshes-lt-100-original-scratch	.081
425	mobilenet_v2_0.5_128	.028
426	unet_entire
427	mobilenet_v2_0.35_160
428	fitvid_trained_on_physion
429	openclip
430	resnext101_32x32d_wsl
431	resnext101_32x48d_wsl
432	resnet50_ImageNet
433	resnet_101_v1
434	resnet_152_v2
435	regnet_y_400mf
436	tv_efficientnet-b1
437	alexnet_ks_torevert
438	yudixie_resnet50_imagenet1kpret_0_240312
439	resnet_152_v1
440	ViT_L_32_imagenet1k
441	resnext101_32x16d_wsl
442	densenet_201_pytorch
443	inception_v3_pytorch
444	pnasnet_large_pytorch
445	mobilevit_small
446	inception_v4
447	nasnet_large
448	deit_small_imagenet_1_seed-0
449	pnasnet_large
450	vonegrcnn_62e_nobn
451	resnet_101_v2
452	vonegrcnn_52e_full
453	pr1_stl10_disentangled_alpha04
454	predictive_coding_pc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance