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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	alexnet	.926
36	yudixie_resnet50_distance_rotation_0_240908	.925
37	yudixie_resnet50_distance_reg_0_240908	.924
38	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.923
39	0.5x_resnet-18_LC	.923
40	resnet-18-LC_m	.922
41	alexnet_random_linf8_perturb	.921
42	grcnn_robust_v1	.921
43	resnet-18-LC_w_sh_1_iter_m	.919
44	resnet50_primary_visual_cortex	.919
45	resnet18_ecoset_full	.918
46	cvt_cvt-21-384-in1k_4_LucyV4	.917
47	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.916
48	AdvProp_efficientnet-b8	.915
49	vgg-16-keras	.916
50	yudixie_resnet50_distance_translation_0_240908	.912
51	resnet-18-LC_w_sh_10_iter_conv_init_m	.912
52	inception_v3-tf	.912
53	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.911
54	convnext_base:clip_laiona_augreg_ft_in1k_384	.909
55	compact_cornets_V4	.909
56	resnet-50_v1-tf	.909
57	grcnn	.908
58	mobilenet_v2_1.0_96	.906
59	blt_vs	.907
60	alexnet_robust_correct	.905
61	resnext101_32x8d_wsl	.903
62	grcnn_109	.902
63	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.900
64	BiT-S-R50x3	.897
65	alexnet_early_checkpoint	.899
66	grcnn_v2_text_noise	.898
67	BiT-S-R101x3	.895
68	nasnet_large-tf	.896
69	compact_resnet50_IT	.895
70	resnet18_imagenet21kP	.896
71	densenet-201-keras	.893
72	mobilenet_v2_1.3_224-tf	.893
73	mobilenet_v2_1.0_160-tf	.892
74	yudixie_resnet50_translation_reg_0_240908	.892
75	resnet50_byol	.892
76	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.890
77	0.5x_resnet-18_LC_w_sh_10_iter	.890
78	yudixie_resnet50_object_class_0_240908	.889
79	alexnet_reduced_aliasing_early_checkpoint	.889
80	resnet50_ewconplus_wzc	.889
81	mobilenet_v2_0_75_192	.887
82	resnet50_imagenet_10_seed-0	.884
83	convnext_tiny_sup	.885
84	AdvProp_efficientnet-b7	.884
85	compact_resnet50_robust_V4	.883
86	resnet-18-LC_w_sh_100_iter_conv_init_m	.882
87	alexnet_l2_3_robust	.882
88	ReAlnet01_cornet_fov16	.882
89	yudixie_resnet18_distance_rotation_0_240719	.882
90	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
91	compact_resnet50_robust_IT	.879
92	resnet101	.878
93	yudixie_resnet18_object_class_0_240719	.878
94	AlexNet_SIN_fov4	.877
95	squeezenet1_1	.877
96	densenet-201	.876
97	mobilenet_v1_1.0_128	.875
98	focalnet_tiny_lrf_in1k	.875
99	alexnet_linf_8_robust	.873
100	efficientnet_b0	.874
101	antialias-resnet152	.873
102	resnet_50_v2	.872
103	ReAlnet02	.872
104	ReAlnet02_cornet	.871
105	yudixie_resnet18_distance_translation_0_240719	.871
106	ReAlnet04	.871
107	ReAlnet03	.870
108	ReAlnet03_cornet	.867
109	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.868
110	ReAlnet04_cornet	.868
111	alexnet	.866
112	alexnet-baseline	.864
113	alexnet	.865
114	alexnet	.865
115	alexnet	.864
116	alexnet	.865
117	alexnet	.865
118	alexnet_workflow_trigger	.865
119	alexnet	.865
120	alexnet	.865
121	yudixie_resnet18_distance_translation_rotation_0_240719	.864
122	0.5x_resnet-18_LC_w_sh_100_iter	.865
123	inception_v3	.863
124	AlexNet_SIN	.863
125	resnet50-vitoimagevidnet8	.863
126	ReAlnet05	.863
127	ReAlnet05_cornet	.862
128	convnext_xlarge:fb_in22k_ft_in1k	.862
129	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.862
130	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.861
131	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.861
132	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.862
133	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.861
134	omnivore_swinS	.862
135	resnet50-simclr-vissl	.861
136	ReAlnet01	.861
137	squeezenet1_0	.859
138	alexnet_fov16	.858
139	ReAlnet01_cornet	.858
140	AdvProp_efficientnet-b4	.858
141	mobilenet_v2_0_5_224	.858
142	mobilenet_v1_0.5_128	.857
143	ReAlnet08	.857
144	ReAlnet08_cornet	.857
145	ReAlnet07_cornet	.857
146	ReAlnet07	.857
147	resnet_50_v1_spiking_l4a	.855
148	ReAlnet09	.856
149	resnet_50_v1	.856
150	resnet_50_v1_spiking_l4	.856
151	resnet50-sup	.856
152	yudixie_resnet50_imagenet1kpret_0_240908	.855
153	ReAlnet09_cornet	.855
154	resnet50_tutorial	.855
155	resnet_50_v1_spiking_l3	.854
156	imagenet_l2_3_0	.855
157	ReAlnet10_cornet	.854
158	resnet_50_v1_spiking	.854
159	ReAlnet10	.852
160	alexnet_fov4	.852
161	resnet50-moclr8deg	.850
162	resnet50-vicregl0p9	.850
163	convnext_base_imagenet_full_seed-0	.848
164	convnext_tiny_imagenet_full_seed-0	.847
165	mobilenet_v2_1_0_128	.847
166	ReAlnet06_cornet	.845
167	ReAlnet06	.845
168	mobilenet_v2_0.35_192	.843
169	inception_v4-tf	.843
170	inception_v2-tf	.843
171	CLIP-RN50	.840
172	vonegrcnn_62e_nobn	.840
173	resnet50_random_linf8_perturb	.838
174	resnet-50-robust	.838
175	resnet50_robust_l2_eps1	.837
176	0.5x_resnet-18	.836
177	mobilenet_v1_0.5_160	.835
178	resnet50-vicregl0p75	.835
179	BiT-M-R101x1	.835
180	convnext_small_imagenet_100_seed-0	.835
181	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.833
182	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.833
183	resnet_SIN_IN_FT_IN	.832
184	mobilenet_v2_1_3_224	.832
185	mobilenet_v2_0.75_192-tf	.830
186	mobilenet_v2_1_4_224	.831
187	imagenet_l2_10_0	.831
188	resnet-18-LC_w_sh_10_iter_m	.830
189	Res2Net50_26w_4s	.830
190	CORnet-Z	.828
191	resnet101_imagenet_full	.826
192	omnivore_swinB	.825
193	resnet50_l2_3_robust	.825
194	resnet50	.822
195	antialiased-r50	.820
196	resnet18-supervised	.819
197	vgg-19-keras	.818
198	convnext_large_imagenet_full_seed-0	.818
199	alexnet_fov12	.818
200	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.817
201	resnet50_linf_8_robust	.817
202	AlexNet_SIN_fov12	.816
203	mobilenet_v2_0.5_96	.814
204	0.5x_resnet-18_LC_w_sh_1_iter	.813
205	resnet50-SIN_IN	.814
206	vit_base_patch16_clip_224:openai_ft_in1k	.813
207	resnet50-SIN_IN_IN	.813
208	resnet50_robust_l2_eps3	.812
209	mobilenet_v2_1.4_224-tf	.811
210	RN50	.812
211	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.809
212	resnet50_random_l2_perturb	.810
213	cornet_s	.808
214	CORnet-S	.806
215	vonealexnet_gaussian_noise_std4_fixed	.806
216	BiT-S-R152x2	.803
217	ReAlnet07_ALL	.802
218	resnet50_linf_4_robust	.800
219	ReAlnet08_ALL	.800
220	densenet-169	.799
221	ReAlnet04_ALL	.798
222	convnext_small_imagenet_full_seed-0	.797
223	resnet-50x2_untrained	.797
224	AdvProp_efficientnet-b0	.796
225	ReAlnet06_ALL	.793
226	resnet50-SIN	.792
227	ReAlnet03_ALL	.792
228	ReAlnet02_ALL	.791
229	resnet-50_untrained	.791
230	ReAlnet10_ALL	.791
231	texture_shape_resnet50_trained_on_SIN	.791
232	resnet-101_v2-tf	.790
233	ReAlnet05_ALL	.789
234	ReAlnet01_ALL	.788
235	ReAlnet01_cornet_fov12	.787
236	resnet-18_untrained	.788
237	CLIP_resnet50_float32	.788
238	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.787
239	r3m_resnet34_nocrop	.787
240	CLIP_resnet50	.785
241	resnet-50_v2-tf	.786
242	compact_vgg19_IT	.786
243	ReAlnet09_ALL	.785
244	resnet34_imagenet_full	.777
245	yudixie_resnet18_imagenet1kpret_0_240719	.777
246	SWSL_resnet50	.773
247	resnet50-vicreg	.773
248	resnet-101_v1-tf	.771
249	mobilenet_v2_0.35_96	.769
250	resnet-18_test_m	.766
251	densenet-121	.765
252	convnext_tiny:in12k_ft_in1k	.763
253	resnet152_imagenet_full	.761
254	resnet50_imagenet_full	.760
255	alexnet_training_seed_01_fov16	.760
256	vit_large_patch14_clip_224:laion2b_ft_in1k	.759
257	voneresnet-50-non_stochastic	.759
258	resnet18_imagenet_full	.758
259	deit_small_imagenet_full_seed-0	.757
260	pnasnet_large-tf	.757
261	efficientnet_b0_imagenet_full	.756
262	mobilenet_v2_1.0_192-tf	.754
263	mobilenet_v2_1_0_192	.754
264	resnet34_ecoset_full	.754
265	resnet101_ecoset_full	.749
266	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.747
267	resnet-152_v1-tf	.745
268	mobilenet_v1_0.5_224	.744
269	alexnet_training_seed_01_fov12	.744
270	alexnet_training_seed_07	.743
271	yudixie_resnet18_distance_reg_0_240719	.742
272	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.741
273	mobilenet_v1_0.75_192	.739
274	shufflenet_v2_x1_0	.740
275	cvt_cvt-13-384-in1k_4_LucyV4	.739
276	mobilenet_v2_0_75_224	.738
277	BiT-S-R101x1	.736
278	BiT-M-R101x3	.732
279	AlexNet_SIN_fov16	.732
280	alexnet_training_seed_02	.730
281	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.727
282	FrankRobWobv0	.727
283	voneresnet-50-robust	.727
284	vggface	.727
285	mobilenet_v2_0.5_192-tf	.726
286	yudixie_resnet18_rotation_reg_0_240719	.725
287	resnet50-cifar	.722
288	BiT-M-R152x4	.721
289	antialiased-rnext101_32x8d	.717
290	BiT-S-R152x4	.716
291	resnet50-VITO-8deg-cc	.715
292	vit_base_patch14_reg4_dinov2:lvd142m	.714
293	voneresnet-50	.714
294	resnet152_ecoset_full	.709
295	mobilenet_v1_0.25_224	.709
296	VOneCORnet-S	.708
297	yolos_tiny	.707
298	densenet-121-keras	.703
299	resnet50_FractalDB	.703
300	mobilenet_v1_0.75_224	.701
301	vit_large_patch14_clip_336:laion2b_ft_in1k	.702
302	alexnet_training_seed_04	.700
303	mobilenet_v2_0.75_128	.700
304	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.700
305	mobilenet_v1_0.25_160	.696
306	SWSL_resnext101_32x8d	.695
307	v1-pyr-nodown	.695
308	resnet-18-LC_w_sh_100_iter_m	.694
309	CLIP_ViT-B_32	.693
310	alexnet_training_seed_01	.693
311	mobilenet_v1_1.0_224	.691
312	resnet50_ecoset_full	.691
313	omnivore_swinT	.690
314	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.689
315	densenet-169-keras	.687
316	my-model	.687
317	konkle_alexnetgn_ipcl_ref01_primary_model	.686
318	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.685
319	mobilenet_v2_1-4_224_pytorch	.684
320	alexnet_training_seed_09	.682
321	nasnet_mobile-tf	.681
322	mobilenet_v2_0.35_224	.680
323	mobilenet_v2_0_75_160	.680
324	effnetv2m_custom384	.676
325	resnet50-barlow	.675
326	mobilenet_v2_1.0_128-tf	.674
327	vision_transformer_vit_large_patch16_224	.670
328	mobilenet_v1_0.25_128	.668
329	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.667
330	vit_base_patch14_dinov2:lvd142m	.667
331	mobilenet_v2_1_0_160	.667
332	cv_18_dagger_408_pretrained	.665
333	deit_small_imagenet_100_seed-0	.662
334	mobilenet_v1_0.5_192	.660
335	resnet50	.658
336	resnet50_moco_v2	.658
337	resnet50_simclr	.657
338	custom_model_cv_18_dagger_408	.656
339	artResNet18_1	.655
340	nasnet_mobile	.654
341	mobilenet_v2_1_0_224	.649
342	mobilenet_v1_1.0_192	.648
343	yudixie_resnet50_random_0_240908	.646
344	effnetb1_272x240	.645
345	resnet-18-LC_conv_init_m	.644
346	alexnet_training_seed_10	.645
347	BiT-M-R152x2	.641
348	AdvProp_efficientnet-b2	.627
349	mobilenet_v2_0.75_160-tf	.624
350	AT_efficientnet-b2	.625
351	vonegrcnn_52e_full	.623
352	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.621
353	vit_large_patch14_clip_224:openai_ft_in1k	.621
354	mobilenet_v2_0_5_192	.619
355	vit_relpos_base_patch16_clsgap_224:sw_in1k	.616
356	resnet-152_v2_pytorch	.615
357	convnext_small_imagenet_10_seed-0	.615
358	BiT-M-R50x1	.613
359	yudixie_resnet18_random_0_240719	.610
360	CORnetZ_CIFAR10_bs32_20_04	.605
361	vonegrcnn_47e	.604
362	inception_v1-tf	.600
363	mobilenet_v2_0.5_224-tf	.597
364	mobilenet_v1_1.0_160	.597
365	alexnet_training_seed_03	.596
366	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.591
367	deit_base_imagenet_full_seed-0	.589
368	r3m_resnet34	.590
369	vonegrcnn_47e	.581
370	deit_large_imagenet_full_seed-0	.577
371	mobilenet_v1_0.75_128	.570
372	mobilenet_v1_0.75_160	.565
373	mobilenet_v1_0.25_192	.560
374	mobilenet_v2_0.75_96	.557
375	inception_resnet_v2	.554
376	alexnet_training_seed_01_fov4	.554
377	efficientnet_b2_imagenet_full	.550
378	r3m_resnet50_nocrop	.550
379	hmax	.535
380	r3m_resnet50	.519
381	r3m_resnet18	.516
382	resnet50_pretrained_with_retinal_waves	.515
383	my-model	.493
384	mobilenet_v2_0.75_224-tf	.490
385	alexnet_training_seed_08	.462
386	convnext_small_imagenet_1_seed-0	.459
387	CORnetZ_CIFAR10	.447
388	vit_base_patch16_dinov3:lvd1689m	.446
389	ViT-B/32	.385
390	mobilenet_v2_0.35_128	.375
391	deit_small_imagenet_10_seed-0	.375
392	resnet50_imagenet_1_seed-0	.355
393	alexnet_training_seed_05	.271
394	mobilenet_v2_0.5_160	.271
395	alexnet_training_seed_06	.215
396	resnet-18-LC_untrained	.170
397	resnet50-meshes-lt-100-original-pretrained	.169
398	resnet50-meshes-lt-100-original-scratch	.081
399	mobilenet_v2_0.5_128	.028
400	unet_entire
401	mobilenet_v2_0.35_160
402	fitvid_trained_on_physion
403	openclip
404	resnext101_32x32d_wsl
405	resnext101_32x48d_wsl
406	resnet50_ImageNet
407	resnet_101_v1
408	resnet_152_v2
409	regnet_y_400mf
410	tv_efficientnet-b1
411	alexnet_ks_torevert
412	yudixie_resnet50_imagenet1kpret_0_240312
413	resnet_152_v1
414	ViT_L_32_imagenet1k
415	resnext101_32x16d_wsl
416	densenet_201_pytorch
417	inception_v3_pytorch
418	pnasnet_large_pytorch
419	mobilevit_small
420	inception_v4
421	nasnet_large
422	deit_small_imagenet_1_seed-0
423	pnasnet_large
424	vonegrcnn_62e_nobn
425	resnet_101_v2
426	vonegrcnn_52e_full

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: circular_variance