Zobrazeno 1 - 10
of 420
pro vyhledávání: '"Zakharov, Alexey"'
Autor:
Kurmukov, Anvar, Chernina, Valeria, Gareeva, Regina, Dugova, Maria, Petrash, Ekaterina, Aleshina, Olga, Pisov, Maxim, Shirokikh, Boris, Samokhin, Valentin, Proskurov, Vladislav, Shimovolos, Stanislav, Basova, Maria, Goncahrov, Mikhail, Soboleva, Eugenia, Donskova, Maria, Yaushev, Farukh, Shevtsov, Alexey, Zakharov, Alexey, Saparov, Talgat, Gombolevskiy, Victor, Belyaev, Mikhail
Interpretation of chest computed tomography (CT) is time-consuming. Previous studies have measured the time-saving effect of using a deep-learning-based aid (DLA) for CT interpretation. We evaluated the joint impact of a multi-pathology DLA on the ti
Externí odkaz:
http://arxiv.org/abs/2406.08137
The task of video prediction and generation is known to be notoriously difficult, with the research in this area largely limited to short-term predictions. Though plagued with noise and stochasticity, videos consist of features that are organised in
Externí odkaz:
http://arxiv.org/abs/2212.14376
Autor:
Sajid, Noor, Tigas, Panagiotis, Fountas, Zafeirios, Guo, Qinghai, Zakharov, Alexey, Da Costa, Lancelot
How can artificial agents learn non-reinforced preferences to continuously adapt their behaviour to a changing environment? We decompose this question into two challenges: ($i$) encoding diverse memories and ($ii$) selectively attending to these for
Externí odkaz:
http://arxiv.org/abs/2207.13699
Autor:
Zakharov, Alexey, Pisov, Maxim, Bukharaev, Alim, Petraikin, Alexey, Morozov, Sergey, Gombolevskiy, Victor, Belyaev, Mikhail
Vertebral body compression fractures are early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by radiologists in clinical settings. Prior research on automatic methods of verte
Externí odkaz:
http://arxiv.org/abs/2204.06818
Autor:
Fountas, Zafeirios, Zakharov, Alexey
Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of
Externí odkaz:
http://arxiv.org/abs/2201.05464
Publikováno v:
Tenth International Conference on Learning Representations (ICLR 2022)
Discovery and learning of an underlying spatiotemporal hierarchy in sequential data is an important topic for machine learning. Despite this, little work has been done to explore hierarchical generative models that can flexibly adapt their layerwise
Externí odkaz:
http://arxiv.org/abs/2110.11236
Publikováno v:
Proceedings of the Unsupervised Reinforcement Learning Workshop ICML 2021
Biological agents have meaningful interactions with their environment despite the absence of immediate reward signals. In such instances, the agent can learn preferred modes of behaviour that lead to predictable states -- necessary for survival. In t
Externí odkaz:
http://arxiv.org/abs/2106.04316
In model-based learning, an agent's model is commonly defined over transitions between consecutive states of an environment even though planning often requires reasoning over multi-step timescales, with intermediate states either unnecessary, or wors
Externí odkaz:
http://arxiv.org/abs/2010.01430
Autor:
Vosylius, Vitalis, Wang, Andy, Waters, Cemlyn, Zakharov, Alexey, Ward, Francis, Folgoc, Loic Le, Cupitt, John, Makropoulos, Antonios, Schuh, Andreas, Rueckert, Daniel, Alansary, Amir
Accurate estimation of the age in neonates is essential for measuring neurodevelopmental, medical, and growth outcomes. In this paper, we propose a novel approach to predict the post-menstrual age (PA) at scan, using techniques from geometric deep le
Externí odkaz:
http://arxiv.org/abs/2008.06098
Autor:
Pisov, Maxim, Kondratenko, Vladimir, Zakharov, Alexey, Petraikin, Alexey, Gombolevskiy, Victor, Morozov, Sergey, Belyaev, Mikhail
Vertebral body compression fractures are reliable early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by radiologists in clinical settings. Prior research on automatic methods
Externí odkaz:
http://arxiv.org/abs/2005.11960