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Jose A. Arjona-Medina
Jose A. Arjona-Medina
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Jahr
Speeding up semantic segmentation for autonomous driving
M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...
MLITS, NIPS Workshop 2, 7, 2016
3282016
RUDDER: Return decomposition for delayed rewards
JA Arjona-Medina, M Gillhofer, M Widrich, T Unterthiner, J Brandstetter, ...
arXiv preprint arXiv:1806.07857, 2018
2242018
Explaining and interpreting LSTMs
L Arras, J Arjona-Medina, M Widrich, G Montavon, M Gillhofer, KR Müller, ...
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 211-238, 2019
1012019
Visual scene understanding for autonomous driving using semantic segmentation
M Hofmarcher, T Unterthiner, J Arjona-Medina, G Klambauer, ...
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 285-296, 2019
522019
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
VP Patil, M Hofmarcher, MC Dinu, M Dorfer, PM Blies, J Brandstetter, ...
arXiv preprint arXiv:2009.14108, 2020
412020
Convergence proof for actor-critic methods applied to ppo and rudder
M Holzleitner, L Gruber, J Arjona-Medina, J Brandstetter, S Hochreiter
Transactions on Large-Scale Data-and Knowledge-Centered Systems XLVIII …, 2021
292021
Computational Synteny Block: A framework to identify evolutionary events
JA Arjona-Medina, O Trelles
IEEE transactions on nanobioscience 15 (4), 343-353, 2016
92016
Computational workflow for the fine-grained analysis of metagenomic samples
E Pérez-Wohlfeil, JA Arjona-Medina, O Torreno, E Ulzurrun, O Trelles
BMC genomics 17, 351-361, 2016
82016
Scene-adaptive radar tracking with deep reinforcement learning
M Stephan, L Servadei, J Arjona-Medina, A Santra, R Wille, G Fischer
Machine Learning with Applications 8, 100284, 2022
72022
XAI and Strategy Extraction via Reward Redistribution
MC Dinu, M Hofmarcher, VP Patil, M Dorfer, PM Blies, J Brandstetter, ...
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2020
62020
RUDDER: Return decomposition for delayed rewards (2018)
JA Arjona-Medina, M Gillhofer, M Widrich, T Unterthiner, J Brandstetter, ...
ArXiv https://arxiv. org/abs, 1806
61806
Deep reinforcement learning for optimization at early design stages
L Servadei, JH Lee, JAA Medina, M Werner, S Hochreiter, W Ecker, ...
IEEE Design & Test 40 (1), 43-51, 2022
52022
Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning
L Servadei, J Zheng, J Arjona-Medina, M Werner, V Esen, S Hochreiter, ...
Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD, 37-42, 2020
52020
Refining borders of genome-rearrangements including repetitions
JA Arjona-Medina, O Trelles
BMC genomics 17, 433-445, 2016
22016
MEET: A Monte Carlo Exploration-Exploitation Trade-Off for Buffer Sampling
J Ott, L Servadei, J Arjona-Medina, E Rinaldi, G Mauro, DS Lopera, ...
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
12023
Algorithms and methods for large-scale genome rearrangements identification
JA Arjona Medina
UMA Editorial, 2017
12017
Algorithms and methods for large-scale genome rearrangements identification
JAA Medina
Universidad de Málaga, 2017
2017
High resolution refinement of Large Scale Genomic Rearrangements using repetitions: A case study
JA Arjona-Medina, G Thode, O Trelles
F1000Research 5, 2016
2016
A Two Time-Scale Update Rule Ensuring Convergence of Episodic Reinforcement Learning Algorithms at the Example of RUDDER
MHJA Arjona-Medina, MC Dinu, AVLGS Hochreiter
GECKO-MGV: Web-based layered analysis of multiple genome comparisons including external post-processing services
S Diaz-Del-Pino, J Arjona-Medina, O Torreno, S Benavides, O Trelles
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