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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.2024
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Empowering Advisors: Designing a Dashboard for University Student GuidanceBaucks, F., & Wiskott, L.In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre. Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung. (p. accepted) Wiesbaden, Germany: Springer VS Fachmedien
@inbook{BaucksWiskott2024, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Empowering Advisors: Designing a Dashboard for University Student Guidance}, editor = {Salden, P. and Leschke, J.}, pages = {accepted}, publisher = {Springer VS Fachmedien}, address = {Wiesbaden, Germany}, month = {June}, year = {2024}, }
Baucks, F., & Wiskott, L.. (2024). Empowering Advisors: Designing a Dashboard for University Student Guidance. In P. Salden & Leschke, J. (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre. Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung. (p. accepted). Wiesbaden, Germany: Springer VS Fachmedien.*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response TheoryBaucks, F., Schmucker, R., & Wiskott, L.In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461) New York, NY, USA: Association for Computing Machinery@inproceedings{BaucksSchmuckerWiskott2024b, author = {Baucks, Frederik and Schmucker, Robin and Wiskott, Laurenz}, title = {*Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory}, booktitle = {LAK24: 14th International Learning Analytics and Knowledge Conference}, pages = {450–461}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, month = {March}, year = {2024}, doi = {10.1145/3636555.3636902}, }
Baucks, F., Schmucker, R., & Wiskott, L.. (2024). *Best Paper Nominee* Gaining Insights into Course Difficulty Variations Using Item Response Theory. In LAK24: 14th International Learning Analytics and Knowledge Conference (pp. 450–461). New York, NY, USA: Association for Computing Machinery. http://doi.org/10.1145/3636555.3636902Gaining Insights into Course Difficulty Variations Using Item Response TheoryBaucks, F., Schmucker, R., & Wiskott, L.In Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK′24), Kyoto, Japan (pp. 450–461) New York, NY, USA: Association for Computing Machinery@inproceedings{BaucksSchmuckerWiskott2024, author = {Baucks, Frederik and Schmucker, Robin and Wiskott, Laurenz}, title = {Gaining Insights into Course Difficulty Variations Using Item Response Theory}, booktitle = {Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK′24), Kyoto, Japan}, pages = {450–461}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, year = {2024}, doi = {10.1145/3636555.3636902}, }
Baucks, F., Schmucker, R., & Wiskott, L.. Gaining Insights into Course Difficulty Variations Using Item Response Theory. In Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK′24), Kyoto, Japan (pp. 450–461). New York, NY, USA: Association for Computing Machinery. http://doi.org/10.1145/3636555.3636902tachAId—An interactive tool supporting the design of human-centered AI solutionsBauroth, M., Rath-Manakidis, P., Langholf, V., Wiskott, L., & Glasmachers, T.Frontiers in Artificial Intelligence, 7@article{BaurothRath-ManakidisLangholfEtAl2024, author = {Bauroth, Max and Rath-Manakidis, Pavlos and Langholf, Valentin and Wiskott, Laurenz and Glasmachers, Tobias}, title = {tachAId—An interactive tool supporting the design of human-centered AI solutions}, journal = {Frontiers in Artificial Intelligence}, volume = {7}, year = {2024}, doi = {10.3389/frai.2024.1354114}, }
Bauroth, M., Rath-Manakidis, P., Langholf, V., Wiskott, L., & Glasmachers, T.. (2024). tachAId—An interactive tool supporting the design of human-centered AI solutions. Frontiers in Artificial Intelligence, 7. http://doi.org/10.3389/frai.2024.1354114Ökolopoly: Case Study on Large Action Spaces in Reinforcement LearningEngelhardt, R. C., Raycheva, R., Lange, M., Wiskott, L., & Konen, W.In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 109–123) Cham: Springer Nature Switzerland@inproceedings{EngelhardtRaychevaLangeEtAl2024, author = {Engelhardt, Raphael C. and Raycheva, Ralitsa and Lange, Moritz and Wiskott, Laurenz and Konen, Wolfgang}, title = {Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning}, booktitle = {Machine Learning, Optimization, and Data Science}, editor = {Nicosia, Giuseppe and Ojha, Varun and La Malfa, Emanuele and La Malfa, Gabriele and Pardalos, Panos M. and Umeton, Renato}, pages = {109–123}, publisher = {Springer Nature Switzerland}, address = {Cham}, year = {2024}, }
Engelhardt, R. C., Raycheva, R., Lange, M., Wiskott, L., & Konen, W. (2024). Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning. In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 109–123). Cham: Springer Nature Switzerland.Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation TasksLange, M., Engelhardt, R. C., Konen, W., & Wiskott, L.In eXplainable AI approaches for Deep Reinforcement Learning@inproceedings{LangeEngelhardtKonenEtAl2024, author = {Lange, Moritz and Engelhardt, Raphael C. and Konen, Wolfgang and Wiskott, Laurenz}, title = {Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks}, booktitle = {eXplainable AI approaches for Deep Reinforcement Learning}, year = {2024}, }
Lange, M., Engelhardt, R. C., Konen, W., & Wiskott, L.. (2024). Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks. In eXplainable AI approaches for Deep Reinforcement Learning. Retrieved from https://openreview.net/forum?id=s1oVgaZ3dQ*Best Paper Award* Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A ComparisonLange, M., Krystiniak, N., Engelhardt, R. C., Konen, W., & Wiskott, L.In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 177–191) Cham: Springer Nature Switzerland@inproceedings{LangeKrystiniakEngelhardtEtAl2024, author = {Lange, Moritz and Krystiniak, Noah and Engelhardt, Raphael C. and Konen, Wolfgang and Wiskott, Laurenz}, title = {*Best Paper Award* Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison}, booktitle = {Machine Learning, Optimization, and Data Science}, editor = {Nicosia, Giuseppe and Ojha, Varun and La Malfa, Emanuele and La Malfa, Gabriele and Pardalos, Panos M. and Umeton, Renato}, pages = {177–191}, publisher = {Springer Nature Switzerland}, address = {Cham}, year = {2024}, doi = {10.1007/978-3-031-53966-4_14}, }
Lange, M., Krystiniak, N., Engelhardt, R. C., Konen, W., & Wiskott, L.. (2024). *Best Paper Award* Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison. In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 177–191). Cham: Springer Nature Switzerland. http://doi.org/10.1007/978-3-031-53966-4_14ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource AllocationPendyala, A., Dettmer, J., Glasmachers, T., & Atamna, A.In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 78–92) Cham: Springer Nature Switzerland@inproceedings{PendyalaDettmerGlasmachersEtAl2024, author = {Pendyala, Abhijeet and Dettmer, Justin and Glasmachers, Tobias and Atamna, Asma}, title = {ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation}, booktitle = {Machine Learning, Optimization, and Data Science}, editor = {Nicosia, Giuseppe and Ojha, Varun and La Malfa, Emanuele and La Malfa, Gabriele and Pardalos, Panos M. and Umeton, Renato}, pages = {78–92}, publisher = {Springer Nature Switzerland}, address = {Cham}, year = {2024}, }
Pendyala, A., Dettmer, J., Glasmachers, T., & Atamna, A.. (2024). ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation. In G. Nicosia, Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M., & Umeton, R. (Eds.), Machine Learning, Optimization, and Data Science (pp. 78–92). Cham: Springer Nature Switzerland.ProtoP-OD: Explainable Object Detection with Prototypical PartsRath-Manakidis, P., Strothmann, F., Glasmachers, T., & Wiskott, L.arXiv@misc{Rath-ManakidisStrothmannGlasmachersEtAl2024, author = {Rath-Manakidis, Pavlos and Strothmann, Frederik and Glasmachers, Tobias and Wiskott, Laurenz}, title = {ProtoP-OD: Explainable Object Detection with Prototypical Parts}, year = {2024}, doi = {10.48550/arXiv.2402.19142}, }
Rath-Manakidis, P., Strothmann, F., Glasmachers, T., & Wiskott, L.. (2024). ProtoP-OD: Explainable Object Detection with Prototypical Parts. arXiv. http://doi.org/10.48550/arXiv.2402.19142Classification and Reconstruction Processes in Deep Predictive Coding Networks: Antagonists or Allies?Rathjens, J., & Wiskott, L.arXiv@misc{RathjensWiskott2024, author = {Rathjens, Jan and Wiskott, Laurenz}, title = {Classification and Reconstruction Processes in Deep Predictive Coding Networks: Antagonists or Allies?}, year = {2024}, }
Rathjens, J., & Wiskott, L.. (2024). Classification and Reconstruction Processes in Deep Predictive Coding Networks: Antagonists or Allies? arXiv.2023
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Induction of excitatory brain state governs plastic functional changes in visual cortical topologyEysel, U. T., & Jancke, D.Brain Structure and Function
@article{EyselJancke2023, author = {Eysel, Ulf T. and Jancke, Dirk}, title = {Induction of excitatory brain state governs plastic functional changes in visual cortical topology}, journal = {Brain Structure and Function}, month = {December}, year = {2023}, doi = {10.1007/s00429-023-02730-y}, }
Eysel, U. T., & Jancke, D.. (2023). Induction of excitatory brain state governs plastic functional changes in visual cortical topology. Brain Structure and Function. http://doi.org/10.1007/s00429-023-02730-yWorking memory performance is tied to stimulus complexityPusch, R., Packheiser, J., Azizi, A. H., Sevincik, C. S., Rose, J., Cheng, S., et al.Communications Biology, 6(1)@article{PuschPackheiserAziziEtAl2023, author = {Pusch, Roland and Packheiser, Julian and Azizi, Amir Hossein and Sevincik, Celil Semih and Rose, Jonas and Cheng, Sen and Stüttgen, Maik C. and Güntürkün, Onur}, title = {Working memory performance is tied to stimulus complexity}, journal = {Communications Biology}, volume = {6}, number = {1}, month = {November}, year = {2023}, doi = {10.1038/s42003-023-05486-7}, }
Pusch, R., Packheiser, J., Azizi, A. H., Sevincik, C. S., Rose, J., Cheng, S., et al. (2023). Working memory performance is tied to stimulus complexity. Communications Biology, 6(1). http://doi.org/10.1038/s42003-023-05486-7Response retention and apparent motion effect in visual cortex modelsTiselko, V. S., Volgushev, M., Jancke, D., & Chizhov, A. V.PLOS ONE, 18(11), e0293725@article{TiselkoVolgushevJanckeEtAl2023, author = {Tiselko, Vasilii S. and Volgushev, Maxim and Jancke, Dirk and Chizhov, Anton V.}, title = {Response retention and apparent motion effect in visual cortex models}, journal = {PLOS ONE}, volume = {18}, number = {11}, pages = {e0293725}, month = {November}, year = {2023}, doi = {10.1371/journal.pone.0293725}, }
Tiselko, V. S., Volgushev, M., Jancke, D., & Chizhov, A. V. (2023). Response retention and apparent motion effect in visual cortex models. PLOS ONE, 18(11), e0293725. http://doi.org/10.1371/journal.pone.0293725Tunable synaptic working memory with volatile memristive devicesRicci, S., Kappel, D., Tetzlaff, C., Ielmini, D., & Covi, E.Neuromorphic Computing and Engineering, 3(4), 044004@article{RicciKappelTetzlaffEtAl2023, author = {Ricci, Saverio and Kappel, David and Tetzlaff, Christian and Ielmini, Daniele and Covi, Erika}, title = {Tunable synaptic working memory with volatile memristive devices}, journal = {Neuromorphic Computing and Engineering}, volume = {3}, number = {4}, pages = {044004}, month = {October}, year = {2023}, doi = {10.1088/2634-4386/ad01d6}, }
Ricci, S., Kappel, D., Tetzlaff, C., Ielmini, D., & Covi, E. (2023). Tunable synaptic working memory with volatile memristive devices. Neuromorphic Computing and Engineering, 3(4), 044004. http://doi.org/10.1088/2634-4386/ad01d6Neural dynamic foundations of a theory of higher cognition: the case of grounding nested phrasesSabinasz, D., Richter, M., & Schöner, G.Cognitive Neurodynamics@article{SabinaszRichterSchöner2023, author = {Sabinasz, Daniel and Richter, Mathis and Schöner, Gregor}, title = {Neural dynamic foundations of a theory of higher cognition: the case of grounding nested phrases}, journal = {Cognitive Neurodynamics}, month = {October}, year = {2023}, doi = {10.1007/s11571-023-10007-7}, }
Sabinasz, D., Richter, M., & Schöner, G.. (2023). Neural dynamic foundations of a theory of higher cognition: the case of grounding nested phrases. Cognitive Neurodynamics. http://doi.org/10.1007/s11571-023-10007-7A Tutorial on the Spectral Theory of Markov ChainsSeabrook, E., & Wiskott, L.Neural Computation, 35(11), 1713–1796@article{SeabrookWiskott2023, author = {Seabrook, Eddie and Wiskott, Laurenz}, title = {A Tutorial on the Spectral Theory of Markov Chains}, journal = {Neural Computation}, volume = {35}, number = {11}, pages = {1713–1796}, month = {October}, year = {2023}, doi = {10.1162/neco_a_01611}, }
Seabrook, E., & Wiskott, L.. (2023). A Tutorial on the Spectral Theory of Markov Chains. Neural Computation, 35(11), 1713–1796. http://doi.org/10.1162/neco_a_01611A map of spatial navigation for neuroscienceParra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.Neuroscience & Biobehavioral Reviews, 152, 105200@article{Parra-BarreroVijayabaskaranSeabrookEtAl2023, author = {Parra-Barrero, Eloy and Vijayabaskaran, Sandhiya and Seabrook, Eddie and Wiskott, Laurenz and Cheng, Sen}, title = {A map of spatial navigation for neuroscience}, journal = {Neuroscience & Biobehavioral Reviews}, volume = {152}, pages = {105200}, month = {September}, year = {2023}, doi = {10.1016/j.neubiorev.2023.105200}, }
Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.. (2023). A map of spatial navigation for neuroscience. Neuroscience & Biobehavioral Reviews, 152, 105200. http://doi.org/10.1016/j.neubiorev.2023.105200Hierarchical Transformer VQ-VAE: An investigation of attentional selection in a generative model of episodic memoryReyhanian, S., Fayyaz, Z., & Wiskott, L.Bernstein Conference@misc{ReyhanianFayyazWiskott2023, author = {Reyhanian, Shirin and Fayyaz, Zahra and Wiskott, Laurenz}, title = {Hierarchical Transformer VQ-VAE: An investigation of attentional selection in a generative model of episodic memory}, howpublished = {Bernstein Conference}, month = {September}, year = {2023}, doi = {10.12751/nncn.bc2023.333}, }
Reyhanian, S., Fayyaz, Z., & Wiskott, L.. (2023, September). Hierarchical Transformer VQ-VAE: An investigation of attentional selection in a generative model of episodic memory. Bernstein Conference. http://doi.org/10.12751/nncn.bc2023.333Von der Forschung in die Praxis: Entwicklung eines Dashboards für die StudienberatungBaucks, F., & Wiskott, L.Abstract presented at 2nd Learning AID@unpublished{BaucksWiskott2023b, author = {Baucks, Frederik and Wiskott, Laurenz}, title = {Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung}, month = {August}, year = {2023}, }
Baucks, F., & Wiskott, L.. (2023, August). Von der Forschung in die Praxis: Entwicklung eines Dashboards für die Studienberatung. Abstract presented at 2nd Learning AID.The stabilization of visibility for sequentially presented, low-contrast objects: Experiments and neural field modelHock, H. S., & Schöner, G.Journal of Vision, 23(8), 12–12@article{HockSchöner2023, author = {Hock, Howard S. and Schöner, Gregor}, title = {The stabilization of visibility for sequentially presented, low-contrast objects: Experiments and neural field model}, journal = {Journal of Vision}, volume = {23}, number = {8}, pages = {12–12}, month = {August}, year = {2023}, doi = {10.1167/jov.23.8.12}, }
Hock, H. S., & Schöner, G.. (2023). The stabilization of visibility for sequentially presented, low-contrast objects: Experiments and neural field model. Journal of Vision, 23(8), 12–12. http://doi.org/10.1167/jov.23.8.12A Multisession SLAM Approach for RatSLAMMenezes, M., Muñoz, M., de Freitas, E. P., Cheng, S., de Almeida Neto, A., Ribeiro, P., & Oliveira, A.Journal of Intelligent & Robotic Systems, 108(4)@article{MenezesMuñozde FreitasEtAl2023, author = {Menezes, Matheus and Muñoz, Mauro and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Neto, Areolino and Ribeiro, Paulo and Oliveira, Alexandre}, title = {A Multisession SLAM Approach for RatSLAM}, journal = {Journal of Intelligent & Robotic Systems}, volume = {108}, number = {4}, month = {July }, year = {2023}, doi = {10.1007/s10846-023-01816-3}, }
Menezes, M., Muñoz, M., de Freitas, E. P., Cheng, S., de Almeida Neto, A., Ribeiro, P., & Oliveira, A. (2023). A Multisession SLAM Approach for RatSLAM. Journal of Intelligent & Robotic Systems, 108(4). http://doi.org/10.1007/s10846-023-01816-3Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay trainingGrappolini, E. W., & Subramoney, A.In International Conference on Neuromorphic Systems (ICONS ′23), Santa Fe, NM, USA ACM@inproceedings{GrappoliniSubramoney2023, author = {Grappolini, Edoardo W. and Subramoney, Anand}, title = {Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training}, booktitle = {International Conference on Neuromorphic Systems (ICONS ′23), Santa Fe, NM, USA}, publisher = {ACM}, month = {June}, year = {2023}, }
Grappolini, E. W., & Subramoney, A.. (2023). Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training. In International Conference on Neuromorphic Systems (ICONS ′23), Santa Fe, NM, USA. ACM.Two modes of midfrontal theta suggest a role in conflict and error processingMuralidharan, V., Aron, A. R., Cohen, M. X., & Schmidt, R.NeuroImage, 273, 120107@article{MuralidharanAronCohenEtAl2023, author = {Muralidharan, Vignesh and Aron, Adam R and Cohen, Michael X and Schmidt, Robert}, title = {Two modes of midfrontal theta suggest a role in conflict and error processing}, journal = {NeuroImage}, volume = {273}, pages = {120107}, month = {June}, year = {2023}, doi = {10.1016/j.neuroimage.2023.120107}, }
Muralidharan, V., Aron, A. R., Cohen, M. X., & Schmidt, R.. (2023). Two modes of midfrontal theta suggest a role in conflict and error processing. NeuroImage, 273, 120107. http://doi.org/10.1016/j.neuroimage.2023.120107Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K.Current Biology, 33(9), 1689–1703.e5@article{de JongNejadYoonEtAl2023, author = {de Jong, Laurel Watkins and Nejad, Mohammadreza Mohagheghi and Yoon, Euisik and Cheng, Sen and Diba, Kamran}, title = {Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3}, journal = {Current Biology}, volume = {33}, number = {9}, pages = {1689–1703.e5}, month = {May}, year = {2023}, doi = {10.1016/j.cub.2023.03.032}, }
de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K. (2023). Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3. Current Biology, 33(9), 1689–1703.e5. http://doi.org/10.1016/j.cub.2023.03.032Learning to predict future locations with internally generated theta sequencesParra-Barrero, E., & Cheng, S.PLOS Computational Biology, 19(5), e1011101@article{Parra-BarreroCheng2023, author = {Parra-Barrero, Eloy and Cheng, Sen}, title = {Learning to predict future locations with internally generated theta sequences}, journal = {PLOS Computational Biology}, volume = {19}, number = {5}, pages = {e1011101}, month = {May}, year = {2023}, doi = {10.1371/journal.pcbi.1011101}, }
Parra-Barrero, E., & Cheng, S.. (2023). Learning to predict future locations with internally generated theta sequences. PLOS Computational Biology, 19(5), e1011101. http://doi.org/10.1371/journal.pcbi.1011101Efficient Recurrent Architectures through Activity Sparsity and Sparse Back-Propagation through TimeSubramoney, A., Nazeer, K. K., Schöne, M., Mayr, C., & Kappel, D.In International Conference on Learning Representations@inproceedings{SubramoneyNazeerSchöneEtAl2023, author = {Subramoney, Anand and Nazeer, Khaleelulla Khan and Schöne, Mark and Mayr, Christian and Kappel, David}, title = {Efficient Recurrent Architectures through Activity Sparsity and Sparse Back-Propagation through Time}, booktitle = {International Conference on Learning Representations}, month = {May}, year = {2023}, }
Subramoney, A., Nazeer, K. K., Schöne, M., Mayr, C., & Kappel, D.. (2023). Efficient Recurrent Architectures through Activity Sparsity and Sparse Back-Propagation through Time. In International Conference on Learning Representations. Retrieved from https://openreview.net/forum?id=lJdOlWg8tdNavigation and the efficiency of spatial coding: insights from closed-loop simulationsGhazinouri, B., Nejad, M. M., & Cheng, S.Brain Structure and Function@article{GhazinouriNejadCheng2023, author = {Ghazinouri, Behnam and Nejad, Mohammadreza Mohagheghi and Cheng, Sen}, title = {Navigation and the efficiency of spatial coding: insights from closed-loop simulations}, journal = {Brain Structure and Function}, month = {April}, year = {2023}, doi = {10.1007/s00429-023-02637-8}, }
Ghazinouri, B., Nejad, M. M., & Cheng, S.. (2023). Navigation and the efficiency of spatial coding: insights from closed-loop simulations. Brain Structure and Function. http://doi.org/10.1007/s00429-023-02637-8Efficient Real Time Recurrent Learning through Combined Activity and Parameter SparsityAnand Subramoney,In ICLR 2023 Workshop on Sparse Neural Networks@inproceedings{Anand Subramoney2023, author = {Anand Subramoney}, title = {Efficient Real Time Recurrent Learning through Combined Activity and Parameter Sparsity}, booktitle = {ICLR 2023 Workshop on Sparse Neural Networks}, month = {March}, year = {2023}, doi = {10.48550/arXiv.2303.05641}, }
Anand Subramoney,. (2023). Efficient Real Time Recurrent Learning through Combined Activity and Parameter Sparsity. In ICLR 2023 Workshop on Sparse Neural Networks. http://doi.org/10.48550/arXiv.2303.05641A model of hippocampal replay driven by experience and environmental structure facilitates spatial learningDiekmann, N., & Cheng, S.eLife, 12, e82301@article{DiekmannCheng2023, author = {Diekmann, Nicolas and Cheng, Sen}, title = {A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning}, journal = {eLife}, volume = {12}, pages = {e82301}, month = {March}, year = {2023}, doi = {10.7554/eLife.82301}, }
Diekmann, N., & Cheng, S.. (2023). A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning. eLife, 12, e82301. http://doi.org/10.7554/eLife.82301CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learningDiekmann, N., Vijayabaskaran, S., Zeng, X., Kappel, D., Menezes, M. C., & Cheng, S.Frontiers in Neuroinformatics, 17@article{DiekmannVijayabaskaranZengEtAl2023, author = {Diekmann, Nicolas and Vijayabaskaran, Sandhiya and Zeng, Xiangshuai and Kappel, David and Menezes, Matheus Chaves and Cheng, Sen}, title = {CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning}, journal = {Frontiers in Neuroinformatics}, volume = {17}, month = {March}, year = {2023}, doi = {10.3389/fninf.2023.1134405}, }
Diekmann, N., Vijayabaskaran, S., Zeng, X., Kappel, D., Menezes, M. C., & Cheng, S.. (2023). CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning. Frontiers in Neuroinformatics, 17. http://doi.org/10.3389/fninf.2023.1134405FAM: Relative Flatness Aware MinimizationAdilova, L., Abourayya, A., Li, J., Dada, A., Petzka, H., Egger, J., et al.TAGML2023@article{AdilovaAbourayyaLiEtAl2023, author = {Adilova, Linara and Abourayya, Amr and Li, Jianning and Dada, Amin and Petzka, Henning and Egger, Jan and Kleesiek, Jens and Kamp, Michael}, title = {FAM: Relative Flatness Aware Minimization}, journal = {TAGML2023}, year = {2023}, }
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