Decoding cerebro-spinal signatures of human behavior: Application to motor sequence learning

Autor: N. Kinany, A. Khatibi, O. Lungu, J. Finsterbusch, C. Büchel, V. Marchand-Pauvert, D. Van De Ville, S. Vahdat, J. Doyon

Publikováno v: NeuroImage, Vol 275, Iss , Pp 120174- (2023)

Mapping the neural patterns that drive human behavior is a key challenge in neuroscience. Even the simplest of our everyday actions stem from the dynamic and complex interplay of multiple neural structures across the central nervous system (CNS). Yet

Externí odkaz: https://doaj.org/article/1f673e83def14a31ae74c87a66f4f7d7

Technology and Performance Benchmarks of IQM's 20-Qubit Quantum Computer

Autor: Abdurakhimov, Leonid, Adam, Janos, Ahmad, Hasnain, Ahonen, Olli, Algaba, Manuel, Alonso, Guillermo, Bergholm, Ville, Beriwal, Rohit, Beuerle, Matthias, Bockstiegel, Clinton, Calzona, Alessio, Chan, Chun Fai, Cucurachi, Daniele, Dahl, Saga, Davletkaliyev, Rakhim, Fedorets, Olexiy, Frieiro, Alejandro Gomez, Gao, Zheming, Guldmyr, Johan, Guthrie, Andrew, Hassel, Juha, Heimonen, Hermanni, Heinsoo, Johannes, Hiltunen, Tuukka, Holland, Keiran, Hotari, Juho, Hsu, Hao, Huhtala, Antti, Hyyppä, Eric, Hämäläinen, Aleksi, Ikonen, Joni, Inel, Sinan, Janzso, David, Jaakkola, Teemu, Jenei, Mate, Jolin, Shan, Juliusson, Kristinn, Jussila, Jaakko, Khalid, Shabeeb, Kim, Seung-Goo, Koistinen, Miikka, Kokkoniemi, Roope, Komlev, Anton, Ockeloen-Korppi, Caspar, Koskinen, Otto, Kotilahti, Janne, Kuisma, Toivo, Kukushkin, Vladimir, Kumpulainen, Kari, Kuronen, Ilari, Kylmälä, Joonas, Lamponen, Niclas, Lamprich, Julia, Landra, Alessandro, Leib, Martin, Li, Tianyi, Liebermann, Per, Lintunen, Aleksi, Liu, Wei, Luus, Jürgen, Marxer, Fabian, de Griend, Arianne Meijer-van, Mitra, Kunal, Moqadam, Jalil Khatibi, Mrożek, Jakub, Mäkynen, Henrikki, Mäntylä, Janne, Naaranoja, Tiina, Nappi, Francesco, Niemi, Janne, Ortega, Lucas, Palma, Mario, Papič, Miha, Partanen, Matti, Penttilä, Jari, Plyushch, Alexander, Qiu, Wei, Rath, Aniket, Repo, Kari, Riipinen, Tomi, Ritvas, Jussi, Romero, Pedro Figueroa, Ruoho, Jarkko, Räbinä, Jukka, Saarinen, Sampo, Sagar, Indrajeet, Sargsyan, Hayk, Sarsby, Matthew, Savola, Niko, Savytskyi, Mykhailo, Selinmaa, Ville, Smirnov, Pavel, Suárez, Marco Marín, Sundström, Linus, Słupińska, Sandra, Takala, Eelis, Takmakov, Ivan, Tarasinski, Brian, Thapa, Manish, Tiainen, Jukka, Tosto, Francesca, Tuorila, Jani, Valenzuela, Carlos, Vasey, David, Vehmaanperä, Edwin, Vepsäläinen, Antti, Vienamo, Aapo, Vesanen, Panu, Välimaa, Alpo, Wesdorp, Jaap, Wurz, Nicola, Wybo, Elisabeth, Yang, Lily, Yurtalan, Ali

Quantum computing has tremendous potential to overcome some of the fundamental limitations present in classical information processing. Yet, today's technological limitations in the quality and scaling prevent exploiting its full potential. Quantum c

Externí odkaz: http://arxiv.org/abs/2408.12433

Automatic Real-word Error Correction in Persian Text

Autor: Dashti, Seyed Mohammad Sadegh, Bardsiri, Amid Khatibi, Shahbazzadeh, Mehdi Jafari

Automatic spelling correction stands as a pivotal challenge within the ambit of natural language processing (NLP), demanding nuanced solutions. Traditional spelling correction techniques are typically only capable of detecting and correcting non-word

Externí odkaz: http://arxiv.org/abs/2407.14795

Using an Evaluator Fixed Structure Learning Automata in Sampling of Social Networks

Autor: S. Roohollahi, A. Khatibi Bardsiri, F. Keynia

Publikováno v: Journal of Artificial Intelligence and Data Mining, Vol 8, Iss 1, Pp 127-148 (2020)

Social networks are streaming, diverse and include a wide range of edges so that continuously evolves over time and formed by the activities among users (such as tweets, emails, etc.), where each activity among its users, adds an edge to the network

Externí odkaz: https://doaj.org/article/c05de232199e4344b9ca59b4a71ce2f6

ALCM: Autonomous LLM-Augmented Causal Discovery Framework

Autor: Khatibi, Elahe, Abbasian, Mahyar, Yang, Zhongqi, Azimi, Iman, Rahmani, Amir M.

To perform effective causal inference in high-dimensional datasets, initiating the process with causal discovery is imperative, wherein a causal graph is generated based on observational data. However, obtaining a complete and accurate causal graph p

Externí odkaz: http://arxiv.org/abs/2405.01744