output
20162025
most citedEfficient Training for Positive Unlabeled Learning

74 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

7 papers

physics.med-ph2025★ 2 cited

Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography

Maxime Descoteaux, Kurt G. Schilling, Dogu Baran Aydogan +44

In the spirit of the historic Millennium Prize Problems that heralded a new era for mathematics, the newly formed International Society for Tractography (IST) has launched the Mill…

cs.CV2022★ 6 cited

Hyperspectral and LiDAR data for the prediction via machine learning of tree species, volume and biomass: a possible contribution for updating forest management plans

Daniele Michelini, Michele Dalponte, Angelo Carriero +4

This work intends to lay the foundations for identifying the prevailing forest types and the delineation of forest units within private forest inventories in the Autonomous Provinc…

astro-ph.EP2021★ 14 cited

Orbit determination just from historical observations? Test case: The comet of AD 760 is identified as 1P/Halley

D. L. Neuhäuser, R. Neuhäuser, M. Mugrauer +2

Recent advances in techniques of critical close reading of historical texts can now be applied to records of pre-telescopic celestial observations - allowing significant progress f…

astro-ph.SR2021★ 5 cited

Critical comments on publications by S. Hoffmann and N. Vogt on historical novae/supernovae and their candidates

R. Neuhäuser, D. L. Neuhäuser

We critically discuss recent articles by S. Hoffmann and N. Vogt on historical novae and supernovae (SNe) as well as their list of `24 most promising events' `with rather high prob…

cs.CV2020★ 17 cited

TriGAN: Image-to-Image Translation for Multi-Source Domain Adaptation

Subhankar Roy, Aliaksandr Siarohin, Enver Sangineto +2

Most domain adaptation methods consider the problem of transferring knowledge to the target domain from a single source dataset. However, in practical applications, we typically ha…

cs.CV2019★ 52 cited

Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

Hao Tang, Hong Liu, Nicu Sebe

We propose a unified Generative Adversarial Network (GAN) for controllable image-to-image translation, i.e., transferring an image from a source to a target domain guided by contro…

cs.LG2016★ 74 cited

Efficient Training for Positive Unlabeled Learning

Emanuele Sansone, Francesco G. B. De Natale, Zhi-Hua Zhou

Positive unlabeled (PU) learning is useful in various practical situations, where there is a need to learn a classifier for a class of interest from an unlabeled data set, which ma…