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Gedächtnisverbesserung: Möglichkeiten und kritische BetrachtungCheng, S.In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus. Bielefeld: transcript Verlag
@incollection{Cheng0, author = {Cheng, Sen}, title = {Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung}, booktitle = {Die Grenze "Mensch". Diskurse des Transhumanismus.}, editor = {Hüttemann, Felix and Liggieri, Kevin}, publisher = {transcript Verlag}, address = {Bielefeld}, year = {in press}, }Cheng, S. (in press). Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung. In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus.. Bielefeld: transcript Verlag.Scene memory and spatial inhibition in visual search - A neural dynamic process model and new experimental evidenceGrieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.Attention, Perception, & Psychophysics, accepted@article{GriebenTekülveZibnerEtAl0, author = {Grieben, Raul and Tekülve, Jan and Zibner, Stephan K.U. and Lins, Jonas and Schneegans, Sebastian and Schöner, Gregor}, title = {Scene memory and spatial inhibition in visual search - A neural dynamic process model and new experimental evidence}, journal = {Attention, Perception, & Psychophysics}, volume = {accepted}, year = {in press}, }Grieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.. (in press). Scene memory and spatial inhibition in visual search - A neural dynamic process model and new experimental evidence. Attention, Perception, & Psychophysics, accepted.2020
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How do memory modules differentially contribute to familiarity and recollection?Hakobyan, O., & Cheng, S.Behavioral and Brain Sciences, 42, e288
@article{HakobyanCheng2020, author = {Hakobyan, Olya and Cheng, Sen}, title = {How do memory modules differentially contribute to familiarity and recollection?}, journal = {Behavioral and Brain Sciences}, volume = {42}, pages = {e288}, year = {2020}, doi = {10.1017/S0140525X19001833}, }Hakobyan, O., & Cheng, S.. (2020). How do memory modules differentially contribute to familiarity and recollection? Behavioral and Brain Sciences, 42, e288. http://doi.org/10.1017/S0140525X19001833Analyzing Reinforcement Learning Benchmarks with Random Weight GuessingOller, D., Cuccu, G., & Glasmachers, T.In International Conference on Autonomous Agents and Multi-Agent Systems@inproceedings{OllerCuccuGlasmachers2020, author = {Oller, Declan and Cuccu, Giuseppe and Glasmachers, Tobias}, title = {Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing}, booktitle = {International Conference on Autonomous Agents and Multi-Agent Systems}, year = {2020}, }Oller, D., Cuccu, G., & Glasmachers, T.. (2020). Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing. In International Conference on Autonomous Agents and Multi-Agent Systems.2019
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Improved graph-based SFA: information preservation complements the slowness principleEscalante-B., A. N., & Wiskott, L.Machine Learning
@article{Escalante-B.Wiskott2019, author = {Escalante-B., Alberto N. and Wiskott, Laurenz}, title = {Improved graph-based SFA: information preservation complements the slowness principle}, journal = {Machine Learning}, month = {December}, year = {2019}, doi = {10.1007/s10994-019-05860-9}, }Escalante-B., A. N., & Wiskott, L.. (2019). Improved graph-based SFA: information preservation complements the slowness principle. Machine Learning. http://doi.org/10.1007/s10994-019-05860-9Hippocampal Reactivation Extends for Several Hours Following Novel ExperienceGiri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K.The Journal of Neuroscience, 39(5), 866–875@article{GiriMiyawakiMizusekiEtAl2019, author = {Giri, Bapun and Miyawaki, Hiroyuki and Mizuseki, Kenji and Cheng, Sen and Diba, Kamran}, title = {Hippocampal Reactivation Extends for Several Hours Following Novel Experience}, journal = {The Journal of Neuroscience}, volume = {39}, number = {5}, pages = {866–875}, month = {December}, year = {2019}, doi = {10.1523/jneurosci.1950-18.2018}, }Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K. (2019). Hippocampal Reactivation Extends for Several Hours Following Novel Experience. The Journal of Neuroscience, 39(5), 866–875. http://doi.org/10.1523/jneurosci.1950-18.2018Improving sensory representations using episodic memoryGörler, R., Wiskott, L., & Cheng, S.Hippocampus@article{GörlerWiskottCheng2019, author = {Görler, Richard and Wiskott, Laurenz and Cheng, Sen}, title = {Improving sensory representations using episodic memory}, journal = {Hippocampus}, month = {December}, year = {2019}, doi = {10.1002/hipo.23186}, }Görler, R., Wiskott, L., & Cheng, S.. (2019). Improving sensory representations using episodic memory. Hippocampus. http://doi.org/10.1002/hipo.23186Computer mouse tracking reveals motor signatures in a cognitive task of spatial language groundingLins, J., & Schöner, G.Attention, Perception, & Psychophysics@article{LinsSchöner2019, author = {Lins, Jonas and Schöner, Gregor}, title = {Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding}, journal = {Attention, Perception, & Psychophysics}, month = {September}, year = {2019}, doi = {10.3758/s13414-019-01847-9}, }Lins, J., & Schöner, G.. (2019). Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding. Attention, Perception, & Psychophysics. http://doi.org/10.3758/s13414-019-01847-9Moment Vector Encoding of Protein Sequences for Supervised ClassificationAltartouri, H., & Glasmachers, T.In Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (pp. 25–35) Springer International Publishing@incollection{AltartouriGlasmachers2019, author = {Altartouri, Haneen and Glasmachers, Tobias}, title = {Moment Vector Encoding of Protein Sequences for Supervised Classification}, booktitle = {Practical Applications of Computational Biology and Bioinformatics, 13th International Conference}, pages = {25–35}, publisher = {Springer International Publishing}, month = {June}, year = {2019}, doi = {10.1007/978-3-030-23873-5_4}, }Altartouri, H., & Glasmachers, T.. (2019). Moment Vector Encoding of Protein Sequences for Supervised Classification. In Practical Applications of Computational Biology and Bioinformatics, 13th International Conference (pp. 25–35). Springer International Publishing. http://doi.org/10.1007/978-3-030-23873-5_4CaMello-XR enables visualization and optogenetic control of Gq/11 signals and receptor trafficking in GPCR-specific domainsEickelbeck, D., Karapinar, R., Jack, A., Suess, S. T., Barzan, R., Azimi, Z., et al.Communications Biology, 2(1)@article{EickelbeckKarapinarJackEtAl2019, author = {Eickelbeck, Dennis and Karapinar, Raziye and Jack, Alexander and Suess, Sandra T. and Barzan, Ruxandra and Azimi, Zohre and Surdin, Tatjana and Grömmke, Michelle and Mark, Melanie D. and Gerwert, Klaus and Jancke, Dirk and Wahle, Petra and Spoida, Katharina and Herlitze, Stefan}, title = {CaMello-XR enables visualization and optogenetic control of Gq/11 signals and receptor trafficking in GPCR-specific domains}, journal = {Communications Biology}, volume = {2}, number = {1}, month = {February}, year = {2019}, doi = {10.1038/s42003-019-0292-y}, }Eickelbeck, D., Karapinar, R., Jack, A., Suess, S. T., Barzan, R., Azimi, Z., et al. (2019). CaMello-XR enables visualization and optogenetic control of Gq/11 signals and receptor trafficking in GPCR-specific domains. Communications Biology, 2(1). http://doi.org/10.1038/s42003-019-0292-yEmerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al.Behavioural Brain Research, 356, 423–434@article{AziziPuschKoenenEtAl2019, author = {Azizi, Amir Hossein and Pusch, Roland and Koenen, Charlotte and Klatt, Sebastian and Bröcker, Franziska and Thiele, Samuel and Kellermann, Janosch and Güntürkün, Onur and Cheng, Sen}, title = {Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)}, journal = {Behavioural Brain Research}, volume = {356}, pages = {423–434}, month = {January}, year = {2019}, doi = {10.1016/j.bbr.2018.05.014}, }Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al. (2019). Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia). Behavioural Brain Research, 356, 423–434. http://doi.org/10.1016/j.bbr.2018.05.0146DoF Vehicle Pose Estimation Using Segmentation-Based Part CorrespondencesBarowski, T., Szczot, M., & Houben, S.In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 573–580)@inproceedings{BarowskiSzczotHouben2019, author = {Barowski, Thomas and Szczot, Magdalena and Houben, Sebastian}, title = {6DoF Vehicle Pose Estimation Using Segmentation-Based Part Correspondences}, booktitle = {Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC)}, pages = {573–580}, year = {2019}, }Barowski, T., Szczot, M., & Houben, S.. (2019). 6DoF Vehicle Pose Estimation Using Segmentation-Based Part Correspondences. In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 573–580).A Parallel RatSlam C++ Library Implementationde Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Neto, A., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R.In Communications in Computer and Information Science (pp. 173–183) Springer International Publishing@incollection{de Souza MuñozMenezesde FreitasEtAl2019, author = {de Souza Muñoz, Mauro Enrique and Menezes, Matheus Chaves and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Neto, Areolino and de Oliveira, Alexandre César Muniz and de Almeida Ribeiro, Paulo Rogério}, title = {A Parallel RatSlam C++ Library Implementation}, booktitle = {Communications in Computer and Information Science}, pages = {173–183}, publisher = {Springer International Publishing}, year = {2019}, doi = {10.1007/978-3-030-36636-0_13}, }de Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Neto, A., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R. (2019). A Parallel RatSlam C++ Library Implementation. In Communications in Computer and Information Science (pp. 173–183). Springer International Publishing. http://doi.org/10.1007/978-3-030-36636-0_13Challenges of Convex Quadratic Bi-objective Benchmark ProblemsGlasmachers, T.In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 559–567) ACM@inproceedings{Glasmachers2019b, author = {Glasmachers, Tobias}, title = {Challenges of Convex Quadratic Bi-objective Benchmark Problems}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)}, pages = {559–567}, publisher = {ACM}, year = {2019}, }Glasmachers, T. (2019). Challenges of Convex Quadratic Bi-objective Benchmark Problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 559–567). ACM.Global Convergence of the (1+1) Evolution StrategyGlasmachers, T.Evolutionary Computation Journal (ECJ)@article{Glasmachers2019, author = {Glasmachers, T.}, title = {Global Convergence of the (1+1) Evolution Strategy}, journal = {Evolutionary Computation Journal (ECJ)}, year = {2019}, }Glasmachers, T. (2019). Global Convergence of the (1+1) Evolution Strategy. Evolutionary Computation Journal (ECJ).Boosting Reinforcement Learning with Unsupervised Feature ExtractionHakenes, S., & Glasmachers, T.In Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation (pp. 555–566) Springer International Publishing@incollection{HakenesGlasmachers2019, author = {Hakenes, Simon and Glasmachers, Tobias}, title = {Boosting Reinforcement Learning with Unsupervised Feature Extraction}, booktitle = {Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation}, pages = {555–566}, publisher = {Springer International Publishing}, year = {2019}, doi = {10.1007/978-3-030-30487-4_43}, }Hakenes, S., & Glasmachers, T.. (2019). Boosting Reinforcement Learning with Unsupervised Feature Extraction. In Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation (pp. 555–566). Springer International Publishing. http://doi.org/10.1007/978-3-030-30487-4_43Measuring the Data Efficiency of Deep Learning MethodsHlynsson, H., Escalante-B., A., & Wiskott, L.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods SCITEPRESS - Science and Technology Publications@inproceedings{HlynssonEscalante-B.Wiskott2019, author = {Hlynsson, Hlynur and Escalante-B., Alberto and Wiskott, Laurenz}, title = {Measuring the Data Efficiency of Deep Learning Methods}, booktitle = {Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods}, publisher = {SCITEPRESS - Science and Technology Publications}, year = {2019}, doi = {10.5220/0007456306910698}, }Hlynsson, H., Escalante-B., A., & Wiskott, L.. (2019). Measuring the Data Efficiency of Deep Learning Methods. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and Technology Publications. http://doi.org/10.5220/0007456306910698Learning Gradient-Based ICA by Neurally Estimating Mutual InformationHlynsson, H. D. ′ið, & Wiskott, L.In C. Benzmüller & Stuckenschmidt, H. (Eds.), KI 2019: Advances in Artificial Intelligence (pp. 182–187) Cham: Springer International Publishing@inproceedings{HlynssonWiskott2019, author = {Hlynsson, Hlynur Dav′ið and Wiskott, Laurenz}, title = {Learning Gradient-Based ICA by Neurally Estimating Mutual Information}, booktitle = {KI 2019: Advances in Artificial Intelligence}, editor = {Benzmüller, Christoph and Stuckenschmidt, Heiner}, pages = {182–187}, publisher = {Springer International Publishing}, address = {Cham}, year = {2019}, }Hlynsson, H. D. ′ið, & Wiskott, L.. (2019). Learning Gradient-Based ICA by Neurally Estimating Mutual Information. In C. Benzmüller & Stuckenschmidt, H. (Eds.), KI 2019: Advances in Artificial Intelligence (pp. 182–187). Cham: Springer International Publishing.Park marking-based vehicle self-localization with a fisheye topview systemHouben, S., Neuhausen, M., Michael, M., Kesten, R., Mickler, F., & Schuller, F.Journal of Real-Time Image Processing, 16(2), 289–304@article{HoubenNeuhausenMichaelEtAl2019, author = {Houben, Sebastian and Neuhausen, Marcel and Michael, Matthias and Kesten, Robert and Mickler, Florian and Schuller, Florian}, title = {Park marking-based vehicle self-localization with a fisheye topview system}, journal = {Journal of Real-Time Image Processing}, volume = {16}, number = {2}, pages = {289–304}, year = {2019}, }Houben, S., Neuhausen, M., Michael, M., Kesten, R., Mickler, F., & Schuller, F. (2019). Park marking-based vehicle self-localization with a fisheye topview system. Journal of Real-Time Image Processing, 16(2), 289–304.A process account of the UnControlled Manifold uncontrolled manifold structure of joint space variance in pointing movementsMartin, V., Reimann, H., & Schöner, G.Biological Cybernetics@article{MartinReimannSchöner2019, author = {Martin, Valère and Reimann, Hendrik and Schöner, Gregor}, title = {A process account of the UnControlled Manifold uncontrolled manifold structure of joint space variance in pointing movements}, journal = {Biological Cybernetics}, year = {2019}, }Martin, V., Reimann, H., & Schöner, G.. (2019). A process account of the UnControlled Manifold uncontrolled manifold structure of joint space variance in pointing movements. Biological Cybernetics.Fusing Shape-from-Silhouette and the Sparsity Driven Detector for Camera-Based 3D Multi-Object Localization with OcclusionsMichael, M., Horn, D., & Houben, S.In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 1417–1424)@inproceedings{MichaelHornHouben2019, author = {Michael, Matthias and Horn, Daniela and Houben, Sebastian}, title = {Fusing Shape-from-Silhouette and the Sparsity Driven Detector for Camera-Based 3D Multi-Object Localization with Occlusions}, booktitle = {Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC)}, pages = {1417–1424}, year = {2019}, }Michael, M., Horn, D., & Houben, S.. (2019). Fusing Shape-from-Silhouette and the Sparsity Driven Detector for Camera-Based 3D Multi-Object Localization with Occlusions. In Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 1417–1424).Vehicle Shape and Color Classification Using Convolutional NeuralNetworkNafzi, M., Brauckmann, M., & Glasmachers, T.arxiv.org@techreport{NafziBrauckmannGlasmachers2019, author = {Nafzi, Mohamed and Brauckmann, Michael and Glasmachers, Tobias}, title = {Vehicle Shape and Color Classification Using Convolutional NeuralNetwork}, number = {1905.08612}, year = {2019}, }Nafzi, M., Brauckmann, M., & Glasmachers, T.. (2019). Vehicle Shape and Color Classification Using Convolutional NeuralNetwork (No. 1905.08612). arxiv.org.Dual SVM Training on a BudgetQaadan, S., Schüler, M., & Glasmachers, T.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods SCITEPRESS - Science and Technology Publications@inproceedings{QaadanSchülerGlasmachers2019, author = {Qaadan, Sahar and Schüler, Merlin and Glasmachers, Tobias}, title = {Dual SVM Training on a Budget}, booktitle = {Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods}, publisher = {SCITEPRESS - Science and Technology Publications}, year = {2019}, }Qaadan, S., Schüler, M., & Glasmachers, T.. (2019). Dual SVM Training on a Budget. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and Technology Publications.Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical SimulationsReimann, D., Nidadavolu, K., ul Hassan, H., Vajragupta, N., Glasmachers, T., Junker, P., & Hartmaier, A.Frontiers in Materials, 6, 181@article{ReimannNidadavoluul HassanEtAl2019, author = {Reimann, Denise and Nidadavolu, Kapil and ul Hassan, Hamad and Vajragupta, Napat and Glasmachers, Tobias and Junker, Philipp and Hartmaier, Alexander}, title = {Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical Simulations}, journal = {Frontiers in Materials}, volume = {6}, pages = {181}, year = {2019}, doi = {10.3389/fmats.2019.00181}, }Reimann, D., Nidadavolu, K., ul Hassan, H., Vajragupta, N., Glasmachers, T., Junker, P., & Hartmaier, A. (2019). Modeling Macroscopic Material Behavior With Machine Learning Algorithms Trained by Micromechanical Simulations. Frontiers in Materials, 6, 181. http://doi.org/10.3389/fmats.2019.00181SpikeDeeptector: A deep-learning based method for detection of neural spiking activitySaif-ur-Rehman, M., Lienkämper, R., Parpaley, Y., Wellmer, J., Liu, C., Lee, B., et al.Journal of Neural Engineering@article{Saif-ur-RehmanLienkämperParpaleyEtAl2019, author = {Saif-ur-Rehman, Muhammad and Lienkämper, Robin and Parpaley, Yaroslav and Wellmer, Jörg and Liu, Charles and Lee, Brian and Kellis, Spencer and Andersen, Richard and Iossifidis, Ioannis and Glasmachers, Tobias and Klaes, Christian}, title = {SpikeDeeptector: A deep-learning based method for detection of neural spiking activity}, journal = {Journal of Neural Engineering}, year = {2019}, }Saif-ur-Rehman, M., Lienkämper, R., Parpaley, Y., Wellmer, J., Liu, C., Lee, B., et al. (2019). SpikeDeeptector: A deep-learning based method for detection of neural spiking activity. Journal of Neural Engineering.The Dynamics of Neural Populations Capture the Laws of the MindSchöner, G.Topics in Cognitive Science, 1–15@article{Schöner2019, author = {Schöner, Gregor}, title = {The Dynamics of Neural Populations Capture the Laws of the Mind}, journal = {Topics in Cognitive Science}, pages = {1–15}, year = {2019}, doi = {10.1111/tops.12453}, }Schöner, G. (2019). The Dynamics of Neural Populations Capture the Laws of the Mind. Topics in Cognitive Science, 1–15. http://doi.org/10.1111/tops.12453Generation of Natural Traffic Sign Images Using Domain Translation with Cycle-Consistent Generative Adversarial NetworksSpata, D., Horn, D., & Houben, S.In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 622–628)@inproceedings{SpataHornHouben2019, author = {Spata, Dominic and Horn, Daniela and Houben, Sebastian}, title = {Generation of Natural Traffic Sign Images Using Domain Translation with Cycle-Consistent Generative Adversarial Networks}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium (IV)}, pages = {622–628}, year = {2019}, }Spata, D., Horn, D., & Houben, S.. (2019). Generation of Natural Traffic Sign Images Using Domain Translation with Cycle-Consistent Generative Adversarial Networks. In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 622–628).Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented MovementTekülve, J., Fois, A., Sandamirskaya, Y., & Schöner, G.Frontiers in Neurorobotics, 13, 95@article{TekülveFoisSandamirskayaEtAl2019, author = {Tekülve, Jan and Fois, Adrien and Sandamirskaya, Yulia and Schöner, Gregor}, title = {Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented Movement}, journal = {Frontiers in Neurorobotics}, volume = {13}, pages = {95}, year = {2019}, doi = {10.3389/fnbot.2019.00095}, }Tekülve, J., Fois, A., Sandamirskaya, Y., & Schöner, G.. (2019). Autonomous Sequence Generation for a Neural Dynamic Robot: Scene Perception, Serial Order, and Object-Oriented Movement. Frontiers in Neurorobotics, 13, 95. http://doi.org/10.3389/fnbot.2019.00095Neural dynamic concepts for intentional systemsTekülve, J., & Schöner, G.In 41th Annual Conference of the Cognitive Science Society (CogSci 2019)@inproceedings{TekülveSchöner2019, author = {Tekülve, Jan and Schöner, Gregor}, title = {Neural dynamic concepts for intentional systems}, booktitle = {41th Annual Conference of the Cognitive Science Society (CogSci 2019)}, year = {2019}, }Tekülve, J., & Schöner, G.. (2019). Neural dynamic concepts for intentional systems. In 41th Annual Conference of the Cognitive Science Society (CogSci 2019).Autonomously learning beliefs is facilitated by a neural dynamic network driving an intentional agentTekülve, J., & Schöner, G.In Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019 Joint IEEE International Conference on (pp. 143–150) IEEE@inproceedings{TekülveSchöner2019b, author = {Tekülve, Jan and Schöner, Gregor}, title = {Autonomously learning beliefs is facilitated by a neural dynamic network driving an intentional agent}, booktitle = {Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019 Joint IEEE International Conference on}, pages = {143–150}, organization = {IEEE}, year = {2019}, }Tekülve, J., & Schöner, G.. (2019). Autonomously learning beliefs is facilitated by a neural dynamic network driving an intentional agent. In Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019 Joint IEEE International Conference on (pp. 143–150). IEEE.Gradient-based Training of Slow Feature Analysis by Differentiable Approximate WhiteningSchüler, M., Hlynsson, H. D., & Wiskott, L.In Proceedings of The 11th Asian Conference on Machine Learning (Vol. 101, p. To appear) PMLR@inproceedings{SchülerHlynssonWiskott2019, author = {Schüler, Merlin and Hlynsson, Hlynur Davíð and Wiskott, Laurenz}, title = {Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening}, booktitle = {Proceedings of The 11th Asian Conference on Machine Learning}, pages = {To appear}, publisher = {PMLR}, volume = {101}, series = {Proceedings of Machine Learning Research}, month = {}, year = {2019}, }Schüler, M., Hlynsson, H. D., & Wiskott, L.. (2019). Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening. In Proceedings of The 11th Asian Conference on Machine Learning (Vol. 101, p. To appear). PMLR.2018
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A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots SystemsMenezes, M. C., de Freitas, E. P., Cheng, S., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R.In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) IEEE
@inproceedings{Menezesde FreitasChengEtAl2018, author = {Menezes, Matheus Chaves and de Freitas, Edison Pignaton and Cheng, Sen and de Oliveira, Alexandre Cesar Muniz and de Almeida Ribeiro, Paulo Rogerio}, title = {A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems}, booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)}, publisher = {IEEE}, month = {November}, year = {2018}, doi = {10.1109/icarcv.2018.8581270}, }Menezes, M. C., de Freitas, E. P., Cheng, S., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R. (2018). A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems. In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE. http://doi.org/10.1109/icarcv.2018.8581270Autonomous Exploration Guided by Optimisation MetaheuristicSantos, R. G., de Freitas, E. P., Cheng, S., de Almeida Ribeiro, P. R., & de Oliveira, A. C. M.In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) IEEE@inproceedings{Santosde FreitasChengEtAl2018, author = {Santos, Raphael Gomes and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Ribeiro, Paulo Rogerio and de Oliveira, Alexandre Cesar Muniz}, title = {Autonomous Exploration Guided by Optimisation Metaheuristic}, booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)}, publisher = {IEEE}, month = {November}, year = {2018}, doi = {10.1109/icarcv.2018.8581136}, }