<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-ODDEKK4V</identifier><date>2026</date><creator>Šega, Jakob</creator><relation>documents/doc/O/URN_NBN_SI_doc-ODDEKK4V_001.pdf</relation><relation>documents/doc/O/URN_NBN_SI_doc-ODDEKK4V_001.txt</relation><format format_type="volume">13</format><format format_type="extent">18 str.</format><format format_type="issue">2</format><format format_type="type">article</format><identifier identifier_type="ISSN">2385-8567</identifier><identifier identifier_type="COBISSID_HOST">291944963</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-ODDEKK4V</identifier><language>slv</language><publisher publisher_location="Ljubljana">Založba Fakultete za matematiko in fiziko Univerze v Ljubljani</publisher><source>Matrika</source><rights>BY</rights><subject language_type_id="eng">data distribution modeling</subject><subject language_type_id="eng">deep machine learning</subject><subject language_type_id="slv">globoko strojno učenje</subject><subject language_type_id="slv">modeliranje porazdelitve podatkov</subject><subject language_type_id="slv">variacijski samokodirniki</subject><subject language_type_id="eng">variational autoencoders</subject><title>Variacijski samokodirniki kot verjetnostni okvir za ocenjevanje gostote verjetnosti</title></Record>