academia

Current Occupation

  • Master Student in Computer Science (TU Darmstadt)
  • Voluntary Research Associate at the Frankfurt Institute for Advanced Studies
    • Working at FIAS / Triesch Lab on AI, Occluded Object Recognition and Developmental Robotics
    • Interested in AI, Reinforcement Learning, Recurrent Neural Networks

Publications

 

  • Ernst, M. R., López, F. M., Aubret, A., Fleming, R. W., & Triesch, J. (2024, May). Self-Supervised Learning of Color Constancy. In 2024 IEEE International Conference on Development and Learning (ICDL) (pp. 1-7). IEEE.
  • Mattern, D., Schumacher, P., López, F. M., Raabe, M. C., Ernst, M. R., Aubret, A., & Triesch, J. (2024). MIMo: A Multimodal Infant Model for Studying Cognitive Development. IEEE Transactions on Cognitive and Developmental Systems, 16(4), 1291-1301.
  • Aubret A.*, Ernst, M. R.*, Teuliere C., & Triesch, J. (2023). Time to Augment Visual Self-Supervised Learning. In Eleventh International Conference on Learning Representations (ICLR).   (* indicates equal contribution.)
  • Mattern, D., López, F. M., Ernst, M. R., Aubret, A., & Triesch, J. (2022, September). MIMo: A Multi-Modal Infant Model for Studying Cognitive Development in Humans and AIs. In 2022 IEEE International Conference on Development and Learning (ICDL) (pp. 23-29). IEEE.
  • Ernst M. R., Burwick T., Triesch J. (2021) Recurrent processing improves occluded object recognition and gives rise to perceptual hysteresis. Journal of Vision https://doi.org/10.1167/jov.21.13.6.
  • Schneider F., Xu X., Ernst M. R., Yu Z., and Triesch J. (2021), Contrastive Learning Through Time. SVRHM 2021 workshop@NeurIPS.
  • Ernst M. R., Triesch J., Burwick T. (2020). Recurrent Feedback Improves Recognition of Partially Occluded Objects. In Proceedings of the 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN2020)
  • Ernst M. R., Triesch J., Burwick T. (2019) Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders. In: Tetko I., Kůrková V., Karpov P., Theis F. (eds) Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. ICANN 2019. Lecture Notes in Computer Science, vol 11729. Springer, Cham https://doi.org/10.1007/978-3-030-30508-6_24
  • Wagner, A. C., Bergen, A., Brilke, S., Fuchs, C., Ernst, M., Hoker, J., Heinritzi, M., Simon, M., Bühner, B., Curtius, J., and Kürten, A.: Size Resolved Online Chemical Analysis of Nano Aerosol Particles: A Thermal Desorption Differential Mobility Analyzer Coupled to a Chemical Ionization Time Of Flight Mass Spectrometer, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-116, 2018.