Angleraud, A., Houbre, Q., Kyrki, V., & Pieters, R. (2018). Human-robot interactive learning architecture using ontologies and symbol manipulation. teoksessa RO-MAN 2018 - 27th IEEE International Symposium on Robot and Human Interactive Communication: August 27-31, 2018, Nanjing, China. (Sivut 384-389). (IEEE RO-MAN). IEEE.

Angleraud, A., Houbre, Q., & Pieters, R. (2019). Teaching semantics and skills for human-robot collaboration. Paladyn, 10(1), 318-329.

Bron, E. E., Smits, M., van der Flier, W. M., Vrenken, H., Barkhof, F., Scheltens, P., ... Klein, S. (2015). Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge. NeuroImage, 111, 562-579.

Chen, K., & Zhang, Z. (2018). A Primal Neural Network for Online Equality-Constrained Quadratic Programming. Cognitive Computation, 10(2), 381–388.

Faisal, A., Gillberg, J., Leen, G., & Peltonen, J. (2013). Transfer learning using a nonparametric sparse topic model. Neurocomputing, 112, 124-137.

Gavas, R. D., Tripathy, S. R., Chatterjee, D., & Sinha, A. (2018). Cognitive load and metacognitive confidence extraction from pupillary response. Cognitive Systems Research, 52, 325-334.

Iantovics, L. B., Emmert-Streib, F., & Arik, S. (2017). MetrIntMeas a novel metric for measuring the intelligence of a swarm of cooperating agents. Cognitive Systems Research, 45, 17-29.

Iosifidis, A., Tefas, A., & Pitas, I. (2015). Distance-based human action recognition using optimized class representations. Neurocomputing, 161, 47-55.

Iosifidis, A., Tefas, A., & Pitas, I. (2015). DropELM: Fast neural network regularization with Dropout and DropConnect. Neurocomputing, 162, 57-66.

Iosifidis, A., Tefas, A., & Pitas, I. (2014). Regularized extreme learning machine for multi-view semi-supervised action recognition. Neurocomputing, 145, 250-262.

Iosifidis, A. (2015). Extreme learning machine based supervised subspace learning. Neurocomputing, 167, 158–164.

Iosifidis, A., Tefas, A., & Pitas, I. (2013). Learning sparse representations for view-independent human action recognition based on fuzzy distances. Neurocomputing, 121, 344-353.

Lolicato, F., Juhola, H., Zak, A., Postila, P. A., Saukko, A., Rissanen, S., ... Róg, T. (2020). Membrane-Dependent Binding and Entry Mechanism of Dopamine into Its Receptor. ACS Chemical Neuroscience, 11(13), 1914–1924.

Miinalainen, T., Rezaei, A., Us, D., Nüßing, A., Engwer, C., Wolters, C. H., & Pursiainen, S. (2019). A realistic, accurate and fast source modeling approach for the EEG forward problem. NeuroImage, 184(1), 56-67.

Mokkila, S., Postila, P. A., Rissanen, S., Juhola, H., Vattulainen, I., & Róg, T. (2017). Calcium Assists Dopamine Release by Preventing Aggregation on the Inner Leaflet of Presynaptic Vesicles. ACS Chemical Neuroscience, 8(6), 1242-1250.

Moradi, E., Khundrakpam, B., Lewis, J. D., Evans, A. C., & Tohka, J. (2017). Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data. NeuroImage, 144(A), 128–141.

Möttönen, T., Katisko, J., Haapasalo, J., Tähtinen, T., Kiekara, T., Kähärä, V., ... Lehtimäki, K. (2015). Defining the anterior nucleus of the thalamus (ANT) as a deep brain stimulation target in refractory epilepsy: Delineation using 3 T MRI and intraoperative microelectrode recording. NeuroImage: Clinical, 7, 823-829.

Pajarinen, J., Peltonen, J., & Uusitalo, M. A. (2011). Fault tolerant machine learning for nanoscale cognitive radio. Neurocomputing, 74(5), 753-764.

Rimpiläinen, V., Koulouri, A., Lucka, F., Kaipio, J. P., & Wolters, C. H. (2019). Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity. NeuroImage, 188, 252-260.

Sciacca, M. F. M., Romanucci, V., Zarrelli, A., Monaco, I., Lolicato, F., Spinella, N., ... Milardi, D. (2017). Inhibition of Aβ Amyloid Growth and Toxicity by Silybins: The Crucial Role of Stereochemistry. ACS Chemical Neuroscience, 8(8), 1767-1778.

Sun, L., Peräkylä, J., Polvivaara, M., Öhman, J., Peltola, J., Lehtimäki, K., ... Hartikainen, K. M. (2015). Human anterior thalamic nuclei are involved in emotion-attention interaction. NEUROPSYCHOLOGIA, 78, 88-94.

Tran, D. T., Iosifidis, A., & Gabbouj, M. (2018). Improving efficiency in convolutional neural networks with multilinear filters. Neural Networks, 105, 328-339.

Waris, M. A., Iosifidis, A., & Gabbouj, M. (2017). CNN-based edge filtering for object proposals. Neurocomputing, 266, 631-640.

Wortha, S. M., Bloechle, J., Ninaus, M., Kiili, K., Lindstedt, A., Bahnmueller, J., ... Klein, E. (2020). Neurofunctional plasticity in fraction learning: An fMRI training study. Trends in Neuroscience and Education, 21, [100141].

Xiao, L., Liao, B., Li, S., & Chen, K. (2018). Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations. Neural Networks, 98, 102-113.