statistiche ricercatore

Continente	#
EU - Europa	63.332
NA - Nord America	933
AS - Asia	434
SA - Sud America	101
Continente sconosciuto - Info sul continente non disponibili	75
AF - Africa	16
OC - Oceania	2
Totale	64.893

Nazione	#
DE - Germania	63.001
US - Stati Uniti d'America	887
SG - Singapore	185
IT - Italia	143
CN - Cina	108
BR - Brasile	80
RU - Federazione Russa	62
HK - Hong Kong	61
SE - Svezia	53
FR - Francia	28
CA - Canada	19
GB - Regno Unito	15
VN - Vietnam	15
IQ - Iraq	11
BD - Bangladesh	10
IN - India	10
FI - Finlandia	8
JP - Giappone	6
CR - Costa Rica	5
EC - Ecuador	5
TN - Tunisia	5
AR - Argentina	4
CO - Colombia	4
ES - Italia	4
IE - Irlanda	4
PK - Pakistan	4
PR - Porto Rico	4
TR - Turchia	4
TT - Trinidad e Tobago	4
CZ - Repubblica Ceca	3
ID - Indonesia	3
KE - Kenya	3
MX - Messico	3
MY - Malesia	3
NL - Olanda	3
PY - Paraguay	3
UZ - Uzbekistan	3
AM - Armenia	2
AU - Australia	2
BB - Barbados	2
BE - Belgio	2
CI - Costa d'Avorio	2
CL - Cile	2
CW - ???statistics.table.value.countryCode.CW???	2
HN - Honduras	2
NI - Nicaragua	2
PE - Perù	2
PL - Polonia	2
SA - Arabia Saudita	2
AT - Austria	1
AZ - Azerbaigian	1
BO - Bolivia	1
CH - Svizzera	1
DO - Repubblica Dominicana	1
DZ - Algeria	1
EG - Egitto	1
ET - Etiopia	1
GP - Guadalupe	1
GR - Grecia	1
GT - Guatemala	1
IL - Israele	1
KG - Kirghizistan	1
KR - Corea	1
KY - Cayman, isole	1
NG - Nigeria	1
OM - Oman	1
PH - Filippine	1
PT - Portogallo	1
SC - Seychelles	1
SV - El Salvador	1
TW - Taiwan	1
ZA - Sudafrica	1
Totale	64.820

Nome	#
null	63.036
Ensembles of density estimators for positive-unlabeled learning	215
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning	110
How to Turn Your Knowledge Graph Embeddings into Generative Models	104
End-to-end learning of deep spatio-temporal representations for satellite image time series classification	100
null	93
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains	93
Density Estimators for Positive-Unlabeled Learning	92
Sum-Product Autoencoding: Encoding and Decoding Representations using Sum-Product Networks	86
Learning accurate cutset networks by exploiting decomposability	84
Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks	83
Learning Bayesian random cutset forests	82
Sum-Product Network structure learning by efficient product nodes discovery	81
Alternative Variable Splitting Methods to Learn Sum-Product Networks	81
Multi-Label Classification with Cutset Networks	72
null	70
null	67
Encoding and Decoding Representations with Sum- and Max-Product Networks	62
null	61
null	59
Unifying and Understanding Overparameterized Circuit Representations via Low-Rank Tensor Decompositions	54
What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?	47
null	31
null	16
null	14
Totale	64.893

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2021/2022	101	0	0	0	0	9	11	1	12	12	6	15	35
2022/2023	162	20	20	23	10	12	24	2	17	26	1	3	4
2023/2024	47	7	9	3	2	3	6	1	2	1	0	4	9
2024/2025	347	14	5	20	4	7	38	72	24	12	10	63	78
2025/2026	590	81	27	25	27	77	28	77	14	76	79	15	64
2026/2027	171	16	52	32	69	2	0	0	0	0	0	0	0
Totale													64.893