Scientific publications

@inproceedings{Sedys2026,

title = {A Case Study of Detecting Nutrient Deficiencies in Corn Using Multispectral Satellite Imagery},

author = {Gintautas \v{S}edys and Mantas Luko\v{s}evi\v{c}ius and Ernestas Petrauskas and Art\={u}ras Gotceitas and Ernestas Zaleckas and Martynas Grei\v{c}ius},

editor = {Audrius Lopata and Daina Gudonien\.{e} and Jonas \v{C}eponis},

url = {https://mantas.info/get-publication/?f=Detecting_nutrient_deficiencies_in_corn_using_multispectral_satellite_imagery.pdf

https://link.springer.com/chapter/10.1007/978-3-032-16808-5_2},

doi = {10.1007/978-3-032-16808-5_2},

isbn = {978-3-032-16808-5},

year  = {2026},

date = {2026-04-01},

urldate = {2026-04-01},

booktitle = { Information and Software Technologies. ICIST 2025},

pages = {15\textendash26},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {We explore the feasibility of detecting nitrogen deficiencies in a cornfield using exclusively multispectral satellite imagery. Attempts to leverage Sentinel-1 and Sentinel-2 data demonstrate that while nutrient shortages are successfully identified through multi-sensor approaches\textemdash often incorporating UAV imagery, ground-based measurements, or advanced vegetation indices\textemdashreliably detecting these deficits from satellite imagery alone remains challenging. Data scarcity, uneven initial and structural soil conditions, noise introduced by atmospheric effects and cloud cover complicate the direct association of spectral signals with nutrient levels. Despite observed differences in key vegetation indices, such as NDVI, between fertilized and unfertilized plots at late growth stages, early-season detection proved unreliable. These findings illustrate the complexity of detecting nutrient deficiencies and highlight the need for improved data quality, supplementary ground truth measurements, or more sophisticated modeling approaches to enhance the accuracy and accessibility of satellite-only nutrient deficiency detection in precision agriculture.},

keywords = {Geospatial, Precision agriculture},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Butkeviciute2026,

title = {Detecting Stressful Driving Situations Using Wearable PPG Sensors: A Case Study},

author = {Egl\.{e} Butkevi\v{c}i\={u}t\.{e} and Tomas Bla\v{z}auskas and Mindaugas Vasiljevas and Mantas Luko\v{s}evi\v{c}ius and Mikas Binkis and Benas Ranauskas and Dominykas Barisas and Lukas Paulauskas},

editor = {Audrius Lopata and Daina Gudonien\.{e} and Jonas \v{C}eponis},

url = {https://mantas.info/get-publication/?f=Detecting Stressful Driving Situations of Drivers Using Wearable PPG Sensors.pdf

https://link.springer.com/chapter/10.1007/978-3-032-16808-5_21},

doi = {10.1007/978-3-032-16808-5_21},

isbn = {978-3-032-16808-5},

year  = {2026},

date = {2026-04-01},

urldate = {2026-01-01},

booktitle = { Information and Software Technologies. ICIST 2025},

pages = {257\textendash269},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {Stress remains a key issue in long-distance driving, where prolonged periods behind the wheel can lead to fatigue, reduced attention, and increased risk of accidents. This study explores an approach for detecting potentially stressful situations using pulse rate variability (PRV) metrics extracted from photoplethysmography (PPG) signals. Data gathering involved PPG signals with video recordings for validation. After applying a Min\textendashMax standardization to align individual differences, a Z-score method flagged outliers whenever the values of the PRV parameters deviated more than three standard deviations from the mean. Events were only considered if these outliers persisted for at least one second, reducing the impact of brief fluctuations not related to genuine stress. To make the results more interpretable, outliers occurring within three seconds of each other were merged into single episodes. This process provided a clearer picture of sustained stress, rather than isolated spikes. A final comparison with video footage confirmed that many flagged intervals corresponded to visibly tense driver reactions or challenging driving conditions, suggesting a reasonable alignment between physiological data and observable stress cues. In general, the findings highlight the importance of combining PPG-based PRV measurements, time-based outlier clustering, and video validation to detect moments of elevated stress. This integrated methodology has potential in applications such as advanced driver assistance systems, driver training programs, and other interventions aimed at improving safety and reducing risk on long journeys.},

keywords = {Biomedicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Vaitekaitis2026,

title = {Adapting the dynamic model of educational effectiveness for text-based analysis \textendash codebook development and content validation framework},

author = {Jogaila Vaitekaitis and Leonidas Kyriakides and Mantas Luko\v{s}evi\v{c}ius},

url = {https://library.iated.org/view/BOLLINI2026DOY},

doi = {10.21125/inted.2026.1441},

issn = {2340-1079},

year  = {2026},

date = {2026-03-01},

urldate = {2026-03-01},

booktitle = {INTED2026 Proceedings},

pages = {1441},

publisher = {IATED},

address = {Valencia, Spain},

series = {20th International Technology, Education and Development Conference},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StankeviciusLukosevicius2025,

title = {Random Embeddings Baseline for Text-Level NLP Tasks},

author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=Random_embeddings_baseline_for_text_level_NLP_tasks.pdf

https://link.springer.com/chapter/10.1007/978-3-032-00236-5_24

https://github.com/LukasStankevicius/Random-embeddings-baseline-for-text-level-NLP-tasks},

doi = {10.1007/978-3-032-00236-5_24},

isbn = {978-3-032-00236-5},

year  = {2025},

date = {2025-10-14},

urldate = {2025-10-14},

booktitle = {Software Engineering: Emerging Trends and Practices in System Development},

pages = {301\textendash310},

publisher = {Springer Nature Switzerland},

address = {Cham},

keywords = {Deep learning, Natural language processing, Source code available, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Grigaliunas2024,

title = {Inference acceleration for large language models using "stairs" assisted greedy generation},

author = {Domas Grigali\={u}nas and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=LLMs_acceleration_using_stairs_assisted_generation.pdf

https://ceur-ws.org/Vol-3885/paper18.pdf

https://arxiv.org/abs/2407.19947

https://arxiv.org/pdf/2407.19947

https://www.linkedin.com/posts/lukosevicius_generativeai-opensourceai-llm-activity-7224413004539260930-3l3n},

doi = {10.48550/arXiv.2407.19947},

year  = {2024},

date = {2024-07-29},

urldate = {2024-07-29},

booktitle = {CEUR workshop proceedings of the 29th international conference on information society and university studies (IVUS 2024) Kaunas, Lithuania, May 17, 2024},

volume = {3885},

pages = {165--174},

organization = {CEUR-WS},

howpublished = {arXiv},

keywords = {Deep learning, Natural language processing, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Vileikyte2024,

title = {Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models},

author = {Brigita Vileikyt\.{e} and Mantas Luko\v{s}evi\v{c}ius and Lukas Stankevi\v{c}ius},

url = {https://mantas.info/get-publication/?f=Lithuanian_sentiment_analysis_using_LLMs.pdf

https://ceur-ws.org/Vol-3885/paper27.pdf

https://arxiv.org/abs/2407.19914

https://arxiv.org/pdf/2407.19914

https://huggingface.co/brivil1/lithuanian-sentiment-analysis-DistilBERT

https://huggingface.co/brivil1/lithuanian-sentiment-analysis-ByT5

https://www.linkedin.com/posts/lukosevicius_sentiment-analysis-of-lithuanian-online-reviews-activity-7234181985559035906-lUi1},

doi = {10.48550/arXiv.2407.19914},

year  = {2024},

date = {2024-07-29},

urldate = {2024-07-29},

booktitle = {CEUR workshop proceedings of the 29th international conference on information society and university studies (IVUS 2024) Kaunas, Lithuania, May 17, 2024},

volume = {3885},

pages = {249--258},

organization = {CEUR-WS},

howpublished = {arXiv},

keywords = {Deep learning, Natural language processing, Source code available, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {Basketball Board Detection Using YOLO Algorithms},

author = {Juozas \v{S}irmenis and Mantas Luko\v{s}evi\v{c}ius },

url = {https://mantas.info/get-publication/?f=Basketball_Board_Detection_Using_YOLO_Algorithms.pdf

https://ceur-ws.org/Vol-3885/paper26.pdf},

year  = {2024},

date = {2024-07-29},

urldate = {2024-07-29},

booktitle = {CEUR workshop proceedings of the 29th international conference on information society and university studies (IVUS 2024) Kaunas, Lithuania, May 17, 2024},

volume = {3885},

pages = {239--248},

organization = {CEUR-WS},

keywords = {Biomedicine, Convolutional neural networks, Deep learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StankeviciusLukosevicius22gec,

title = {Towards Lithuanian grammatical error correction},

author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},

editor = {Radek Silhavy},

url = {https://mantas.info/get-publication/?f=Towards_Lithuanian_Grammatical_Error_Correction.pdf

https://arxiv.org/abs/2203.09963

https://arxiv.org/pdf/2203.09963.pdf

https://doi.org/10.48550/arXiv.2203.09963

https://link.springer.com/chapter/10.1007/978-3-031-09076-9_44

https://github.com/LukasStankevicius/Towards-Lithuanian-Grammatical-Error-Correction

https://huggingface.co/LukasStankevicius/ByT5-Lithuanian-gec-100h

https://paperswithcode.com/paper/towards-lithuanian-grammatical-error},

doi = {10.1007/978-3-031-09076-9_44},

isbn = {978-3-031-09076-9},

year  = {2022},

date = {2022-07-08},

urldate = {2022-07-08},

booktitle = {Artificial Intelligence Trends in Systems},

pages = {490--503},

publisher = {Springer},

address = {Cham},

keywords = {Deep learning, Natural language processing, Source code available, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StankeviciusLukosevicius2021,

title = {Generating abstractive summaries of Lithuanian news articles using a transformer model},

author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=Generating_Lithuanian_news_summaries.pdf

https://arxiv.org/abs/2105.03279

https://arxiv.org/pdf/2105.03279.pdf

https://link.springer.com/chapter/10.1007/978-3-030-88304-1_27

https://github.com/LukasStankevicius/Generating-abstractive-summaries-of-Lithuanian-news-articles-using-a-transformer-model

https://huggingface.co/LukasStankevicius/t5-base-lithuanian-news-summaries-175

https://paperswithcode.com/paper/generating-abstractive-summaries-of},

doi = {10.1007/978-3-030-88304-1_27},

isbn = {978-3-030-88304-1},

year  = {2021},

date = {2021-10-07},

urldate = {2021-10-07},

booktitle = {International Conference on Information and Software Technologies - ICIST 2021},

pages = {341--352},

publisher = {Springer},

address = {Cham},

keywords = {Deep learning, Natural language processing, Source code available, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{SkarbaliusLukosevicius21,

title = {Automatic programming problem difficulty evaluation \textendash first results},

author = {Art\={u}ras Skarbalius and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=Problem_difficulty_evaluation.pdf

https://link.springer.com/chapter/10.1007/978-3-030-88304-1_12},

doi = {10.1007/978-3-030-88304-1_12},

isbn = {978-3-030-88304-1},

year  = {2021},

date = {2021-10-07},

urldate = {2021-10-07},

booktitle = {ICIST 2021: Information and Software Technologies},

pages = {150--159},

publisher = {Springer},

keywords = {Convolutional neural networks, Deep learning, Natural language processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{RodriguesLukoseviciusMarozas21,

title = {A fast algorithm for facilitating heartbeat annotation in long-term ECG signals},

author = {Ana Rodrigues and Mantas Luko\v{s}evi\v{c}ius and Vaidotas Marozas},

url = {https://mantas.info/get-publication/?f=ECG_beat_clustering.pdf

https://ieeexplore.ieee.org/document/9662850

https://www.cinc.org/2021/Program/accepted/91_Preprint.pdf

https://www.cinc.org/archives/2021/pdf/CinC2021-091.pdf},

doi = {10.23919/CinC53138.2021.9662850},

year  = {2021},

date = {2021-09-14},

urldate = {2021-09-14},

booktitle = {2021 Computing in Cardiology (CinC)},

volume = {48},

pages = {1-4},

publisher = {IEEE},

keywords = {Biomedicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{PeciulisEtal2021,

title = {Automated age-related macular degeneration area estimation \textendash first results},

author = {Rokas Pe\v{c}iulis and Mantas Luko\v{s}evi\v{c}ius and Algimantas Kri\v{s}\v{c}iukaitis and Robertas Petrolis and Dovil\.{e} Buteikien\.{e}},

url = {https://mantas.info/get-publication/?f=Macular_degeneration_estimation_1st_results.pdf

https://arxiv.org/abs/2107.02211

https://arxiv.org/pdf/2107.02211.pdf

http://ceur-ws.org/Vol-2915/paper16.pdf},

year  = {2021},

date = {2021-04-23},

urldate = {2021-04-23},

booktitle = {Proceedings of the 26th International Conference on Information Society and University Studies (IVUS 2021)},

volume = {2915},

pages = {141-149},

publisher = {CEUR},

keywords = {Biomedicine, Convolutional neural networks, Deep learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{SirmenisLukosevicius21,

title = {Tracking basketball shots \textendash preliminary results},

author = {Juozas \v{S}irmenis and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=Tracking_basketball_shots-preliminary.pdf

http://ceur-ws.org/Vol-2915/paper21.pdf},

year  = {2021},

date = {2021-04-23},

urldate = {2021-04-23},

booktitle = {Proceedings of the 26th International Conference on Information Society and University Studies (IVUS 2021)},

volume = {2915},

pages = {181-190},

publisher = {CEUR},

keywords = {Biomedicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{GallicchioLukoseviciusScardopane20,

title = {Frontiers in Reservoir Computing},

author = {Claudio Gallicchio and Mantas Luko\v{s}evi\v{c}ius and Simone Scardapane},

url = {https://mantas.info/get-publication/?f=Frontiers_in_Reservoir_Computing.pdf

https://www.esann.org/sites/default/files/proceedings/2020/ES2020-7.pdf},

isbn = {78-2-87587-074-2},

year  = {2020},

date = {2020-10-02},

booktitle = {ESANN 2020 proceedings, European Symposium on Artificial Neural Networks, Computational  Intelligence and Machine Learning},

keywords = {Reservoir computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StankeviciusLukosevicius20,

title = {Testing pre-trained Transformer models for Lithuanian news clustering},

author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=testing_transformers_on_LT_news_clustering.pdf

https://arxiv.org/abs/2004.03461

https://arxiv.org/pdf/2004.03461

http://ceur-ws.org/Vol-2698/p08.pdf},

issn = {1613-0073},

year  = {2020},

date = {2020-04-23},

urldate = {2020-04-23},

booktitle = {Proceedings of the IVUS 2020},

volume = {2698},

pages = {46-53},

publisher = {CEUR},

address = {Kaunas, Lithuania},

keywords = {Deep learning, Natural language processing, Transformers},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BukauskasLukosevicius20,

title = {Accident localization at the district heating network of Kaunas region using machine learning},

author = {Mantas Bukauskas and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=heating_accident_localization.pdf

http://ceur-ws.org/Vol-2698/p18.pdf},

isbn = {1613-0073},

year  = {2020},

date = {2020-04-23},

booktitle = {Proceedings of the IVUS 2020},

volume = {2698},

pages = {128-137},

publisher = {CEUR},

address = {Kaunas, Lithuania},

keywords = {Geospatial},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{LukoseviciusUselis19,

title = {Efficient cross-validation of echo state networks},

author = {Mantas Luko\v{s}evi\v{c}ius and Arnas Uselis},

url = {https://mantas.info/get-publication/?f=Efficient_CV_of_ESNs.pdf

https://arxiv.org/abs/1908.08450

https://arxiv.org/pdf/1908.08450.pdf

https://link.springer.com/chapter/10.1007/978-3-030-30493-5_12

https://mantas.info/get-publication/?f=Efficient_CV_of_ESNs_slides.pdf },

doi = {10.1007/978-3-030-30493-5_12},

isbn = {978-3-030-30493-5},

year  = {2019},

date = {2019-09-09},

booktitle = {Artificial Neural Networks and Machine Learning \textendash ICANN 2019: Workshop and Special Sessions. ICANN 2019.},

volume = {11731},

pages = {121-133},

publisher = {Springer, Cham},

series = {Lecture Notes in Computer Science},

note = {presentation slides included},

keywords = {Reservoir computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{StankeviciusLukosevicius19,

title = {Lithuanian news clustering using document embeddings},

author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=LT_news_clustering_using_document_embeddings.pdf

https://ceur-ws.org/Vol-2470/p30.pdf},

issn = {2029-4824},

year  = {2019},

date = {2019-04-25},

urldate = {2019-04-25},

booktitle = {Proceedings of the IVUS 2019},

pages = {136-140},

address = {Kaunas, Lithuania},

keywords = {Deep learning, Natural language processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{CiurlionisLukosevicius18,

title = {Nowcasting precipitation using weather radar data for Lithuania: the first results},

author = {Aivaras \v{C}iurlionis and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=nowcasting_LT_weather_1st_results.pdf

http://ceur-ws.org/Vol-2147/p10.pdf},

year  = {2018},

date = {2018-05-28},

urldate = {2018-05-28},

booktitle = {SYSTEM 2018 Symposium for Young Scientists in Technology, Engineering and Mathematics},

volume = {2147},

pages = {55-60},

publisher = {CEUR},

keywords = {Convolutional neural networks, Deep learning, Geospatial},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{KrusnaLukosevicius18,

title = {Predicting Mozart’s next note via echo state networks},

author = {\k{A}\v{z}uolas Kru\v{s}na and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=predicting_Mozart_via_ESN.pdf

http://ceur-ws.org/Vol-2147/p15.pdf},

year  = {2018},

date = {2018-05-28},

booktitle = {SYSTEM 2018 Symposium for Young Scientists in Technology, Engineering and Mathematics},

volume = {2147},

pages = {84-91},

publisher = {CEUR},

keywords = {Reservoir computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ButkusLukosevicius18,

title = {A polite robot: visual handshake recognition using deep learning},

author = {Liutauras Butkus and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=visual_handshake_recognition.pdf

http://ceur-ws.org/Vol-2147/p14.pdf},

year  = {2018},

date = {2018-05-28},

urldate = {2018-05-28},

booktitle = {SYSTEM 2018 Symposium for Young Scientists in Technology, Engineering and Mathematics},

journal = {SYSTEM 2018 Symposium for Young Scientists in Technology, Engineering and Mathematics},

volume = {2147},

pages = {78-83},

publisher = {CEUR},

keywords = {Convolutional neural networks, Deep learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ZokasLukosevicius18,

title = {Human sport activities recognition and registration from portable device},

author = {Bernardas Zokas and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=sport_activities_recognition.pdf

http://ceur-ws.org/Vol-2147/p11.pdf},

year  = {2018},

date = {2018-05-28},

booktitle = {SYSTEM 2018 Symposium for Young Scientists in Technology, Engineering and Mathematics},

volume = {2147},

pages = {61-65},

publisher = {CEUR},

keywords = {Biomedicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{PranckaitisLukosevicius17,

title = {Clustering of Lithuanian news articles},

author = {Vilius Pranckaitis and Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=clustering_LT_news.pdf

http://ceur-ws.org/Vol-1856/p05.pdf},

year  = {2017},

date = {2017-04-01},

booktitle = {Proceedings of the IVUS 2017},

pages = {27-32},

address = {Kaunas, Lithuania},

keywords = {Deep learning, Natural language processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{LukoseviciusMarozas13,

title = {Noninvasive Fetal QRS Detection using Echo State Network},

author = {Mantas Luko\v{s}evi\v{c}ius and Vaidotas Marozas},

url = {https://mantas.info/get-publication/?f=fetal_QRS_with_ESN.pdf

http://cinc.org/archives/2013/pdf/0205.pdf

https://www.physionet.org/content/challenge-2013/1.0.0/papers/0205.pdf

https://ieeexplore.ieee.org/abstract/document/6712447

https://mantas.info/wp/wp-content/uploads/code/fetal_QRS_with_ESN_and_DP_source_code.zip

https://www.physionet.org/content/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/

https://physionet.org/files/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

booktitle = {Proceedings of Computing in Cardiology 2013},

volume = {40},

pages = {205-208},

keywords = {Biomedicine, Reservoir computing, Source code available},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{KrisciukaitisEtal13,

title = {Wearable system concept for monitoring of maternal and fetal heart activity},

author = {Algimantas Kri\v{s}\v{c}iukaitis and Mantas Luko\v{s}evi\v{c}ius and Robertas Petrolis and Vaidotas Marozas and Saulius Daukantas and Vladas Gintautas and Ar\={u}nas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=monitoring_maternal_and_fetal_heart.pdf

http://biomed.ktu.lt/index.php/BME/article/download/466/10},

year  = {2013},

date = {2013-01-01},

booktitle = {Proceedings of the 17th International Conference ``Biomedical Engineering''},

pages = {36-40},

address = {Kaunas},

keywords = {Biomedicine},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Lukosevicius12,

title = {Self-organized reservoirs and their hierarchies},

author = {Mantas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=self-organized_reservoir_hierarchies.pdf

https://link.springer.com/chapter/10.1007%2F978-3-642-33269-2_74

https://www.ai.rug.nl/minds/uploads/Self-organized_reservoir_hierarchies_ICANN12.pdf},

doi = {10.1007/978-3-642-33269-2_74},

year  = {2012},

date = {2012-01-01},

booktitle = {Artificial Neural Networks and Machine Learning \textendash ICANN 2012},

volume = {7552},

pages = {587-595},

publisher = {Springer},

address = {Berlin, Heidelberg},

series = {LNCS},

keywords = {Deep learning, Reservoir computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DaukantasEtal10,

title = {Comparison of "black box" and "gray box" methods for lost data reconstruction in multichannel signals},

author = {Saulius Daukantas and Mantas Luko\v{s}evi\v{c}ius and Vaidotas Marozas and Ar\={u}nas Luko\v{s}evi\v{c}ius},

url = {https://mantas.info/get-publication/?f=black_and_gray_box_signal_reconstruction.pdf

https://pdfs.semanticscholar.org/9e09/2056472fbc787691e9ea1a682c02558c8a66.pdf},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of the 14th International Conference "Biomedical Engineering"},

pages = {135-138},

address = {Kaunas},

keywords = {Biomedicine, Reservoir computing},

pubstate = {published},

tppubtype = {inproceedings}

}