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Vadim Liventsev
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2020 – today
- 2024
- [i6]Vadim Liventsev, Tobias Fritz:
Intensive Care as One Big Sequence Modeling Problem. CoRR abs/2402.17501 (2024) - [i5]Vadim Liventsev, Vivek Kumar, Allmin Pradhap Singh Susaiyah, Zixiu Wu, Ivan Rodin, Asfand Yaar, Simone Balloccu, Marharyta Beraziuk, Sebastiano Battiato, Giovanni Maria Farinella, Aki Härmä, Rim Helaoui, Milan Petkovic, Diego Reforgiato Recupero, Ehud Reiter, Daniele Riboni, Raymond Sterling:
PhilHumans: Benchmarking Machine Learning for Personal Health. CoRR abs/2405.02770 (2024) - 2023
- [c4]Vadim Liventsev
, Anastasiia Grishina
Fully Autonomous Programming with Large Language Models. GECCO 2023: 1146-1155 - [i4]Vadim Liventsev, Anastasiia Grishina, Aki Härmä, Leon Moonen:
Fully Autonomous Programming with Large Language Models. CoRR abs/2304.10423 (2023) - 2021
- [j1]Vadim Liventsev
Towards Effective Patient Simulators. Frontiers Artif. Intell. 4: 798659 (2021) - [c3]Vadim Liventsev, Aki Härmä
Neurogenetic programming framework for explainable reinforcement learning. GECCO Companion 2021: 329-330 - [i3]Vadim Liventsev, Aki Härmä, Milan Petkovic:
BF++: a language for general-purpose neural program synthesis. CoRR abs/2101.09571 (2021) - [i2]Vadim Liventsev, Aki Härmä, Milan Petkovic:
Neurogenetic Programming Framework for Explainable Reinforcement Learning. CoRR abs/2102.04231 (2021) - [i1]Sander de Bruin, Vadim Liventsev, Milan Petkovic:
Autoencoders as Tools for Program Synthesis. CoRR abs/2108.07129 (2021)
2010 – 2019
- 2019
- [c2]Artem Shelmanov
Active Learning with Deep Pre-trained Models for Sequence Tagging of Clinical and Biomedical Texts. BIBM 2019: 482-489 - [c1]Vadim Liventsev
Deep Text Prior: Weakly Supervised Learning for Assertion Classification. ICANN (Workshop) 2019: 243-257
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