BAYESIANDEEPLEARNING.ORG: Keyword Density Checker

Total words: 8489 | 2-word phrases: 2195 | 3-word phrases: 2468 | 4-word phrases: 2564

PAGE INFO

Title	Try to keep the title under 60 characters (46 characters) Bayesian Deep Learning Workshop \| NeurIPS 2021
Description	Try to keep the meta description between 50 - 160 characters (46 characters) Bayesian Deep Learning Workshop \| NeurIPS 2021
Keywords	Meta keywords are not recommended anymore (49 characters) Bayesian,Deep,Learning,Workshop,NeurIPS,NIPS,2021
H1	H1 tag on the page (22 characters) Bayesian Deep Learning

#	Keyword	Frequency	Density
1	bayesian deep learning	8	0.32%
2	bayesian neural network	8	0.32%
3	bayesian neural networks	6	0.24%
4	neural networks paper	6	0.24%
5	page is available	4	0.16%
6	in bayesian deep	4	0.16%
7	workshop page is	4	0.16%
8	is available here	4	0.16%
9	in deep learning	4	0.16%
10	in downstream tasks	3	0.12%
11	extended abstract submission	3	0.12%
12	yee whye teh	3	0.12%
13	models such as	3	0.12%
14	techniques in downstream	3	0.12%
15	bdl techniques in	3	0.12%
16	of bdl techniques	3	0.12%
17	to be a	3	0.12%
18	to join the	3	0.12%
19	inference in bayesian	3	0.12%
20	reliability of bdl	3	0.12%
21	with dimensionality reduction	2	0.08%
22	has previously appeared	2	0.08%
23	of the poster	2	0.08%
24	joost van amersfoort	2	0.08%
25	gintare karolina dziugaite	2	0.08%
26	thang d bui	2	0.08%
27	previously appeared in	2	0.08%
28	appeared in a	2	0.08%
29	the neurips 2021	2	0.08%
30	including the neurips	2	0.08%

#	Keyword	Frequency	Density
1	page is available here	4	0.16%
2	in bayesian deep learning	3	0.12%
3	inference in bayesian deep	3	0.12%
4	reliability of bdl techniques	3	0.12%
5	of bdl techniques in	3	0.12%
6	workshop page is available	3	0.12%
7	bdl techniques in downstream	3	0.12%
8	techniques in downstream tasks	3	0.12%
9	bayesian neural networks paper	3	0.12%
10	or conference including the	2	0.08%
11	need to improve bayesian	2	0.08%
12	to improve bayesian model	2	0.08%
13	improve bayesian model averaging	2	0.08%
14	welcome to join the	2	0.08%
15	are welcome to join	2	0.08%
16	gradient mcmc a hybrid	2	0.08%
17	stochastic gradient mcmc a	2	0.08%
18	all you need to	2	0.08%
19	mcmc a hybrid vi	2	0.08%
20	a hybrid vi and	2	0.08%
21	hybrid vi and mcmc	2	0.08%
22	vi and mcmc approach	2	0.08%
23	at the neurips website	2	0.08%
24	account at the neurips	2	0.08%
25	approximate inference in bayesian	2	0.08%
26	submit papers through your	2	0.08%
27	in variational bayesian neural	2	0.08%
28	uncertainty in deep learning	2	0.08%
29	is all you need	2	0.08%
30	dropout as an information	2	0.08%
31	qixuan feng angelos filos	2	0.08%
32	likelihood with dimensionality reduction	2	0.08%
33	maximum likelihood with dimensionality	2	0.08%
34	exact maximum likelihood with	2	0.08%
35	funnels exact maximum likelihood	2	0.08%
36	tim g j rudner	2	0.08%
37	deep learning such as	2	0.08%
38	an information bottleneck layer	2	0.08%
39	as an information bottleneck	2	0.08%
40	gaussian dropout as an	2	0.08%

#	URL	Whois	Check
1	https://neurips.cc/virtual/2021/workshop/21827	Whois	neurips.cc
2	http://bit.ly/bdl_posters_2021	Whois	bit.ly
3	https://izmailovpavel.github.io/neurips_bdl_competition/	Whois	github.io
4	https://research.yandex.com/shifts	Whois	yandex.com
5	https://www.youtube.com/channel/UC_LBLWLfKk5rMKDOHoO7vPQ	Whois	youtube.com
6	https://openreview.net/group?id=NeurIPS.cc/2021/Workshop/BDL	Whois	openreview.net
7	https://neurips.cc/	Whois	neurips.cc
8	https://openreview.net/group?id=NeurIPS.cc/2021/Workshop/BDL	Whois	openreview.net
9	https://neurips.cc/	Whois	neurips.cc
10	https://html5up.net	Whois	html5up.net