אודות
אני מתעניין במודלים חישוביים של תפיסה, הבנת סצנות בתלת-ממד, הסקה מבוססת סימולציה (Simulation-based inference) ולמידת מכונה עבור גילוי מדעי. אני מתמקד בעיקר בגישות גנרטיביות הממדלות תפיסה כפתרון הסתברותי לבעיות היפוך (Inverse problems).
פרסומים
- Unifying Unsupervised and Offline RL for Fast Adaptation Using World Models, Khapun, D. & Rosenbaum, D., 1 May 2026, In: IEEE Robotics and Automation Letters. 11, 5, p. 5693-5700 8 p.
- Kernel Reboot: Breaking the Boundaries of Neural Tangent Kernels for Neural Fields, Mallak, A., Maalouf, A., Wolf, L., Rus, D. & Rosenbaum, D., 2026, (Accepted/In press) In: IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Osmosis: RGBD Diffusion Prior for Underwater Image Restoration, Nathan, O. B., Levy, D., Treibitz, T. & Rosenbaum, D., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 302-319 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 15120 LNCS).
- SeaThru-NeRF: Neural Radiance Fields in Scattering Media, Levy, D., Peleg, A., Pearl, N., Rosenbaum, D., Akkaynak, D., Korman, S. & Treibitz, T., 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. IEEE Computer Society, p. 56-65 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).
- From data to functa: Your data point is a function and you can treat it like one, Dupont, E., Kim, H., Eslami, S. M. A., Rezende, D. & Rosenbaum, D., 2022, In: Proceedings of Machine Learning Research. 162, p. 5694-5725 32 p.
- Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs, Rosenbaum, D., Garnelo, M., Zielinski, M., Beattie, C., Clancy, E., Huber, A., Kohli, P., Senior, A. W., Jumper, J., Doersch, C., Eslami, S. M. A., Ronneberger, O. & Adler, J., 26 Jun 2021, Machine Learning is Structural Biology workshop, Neural Information Processing Systems (NeurIPS).
- A Neural Network Auction for Group Decision Making over a Continuous Space, Bachrach, Y., Gemp, I., Garnelo, M., Kramar, J., Eccles, T., Rosenbaum, D. & Graepel, T., 2021, Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021. Zhou, Z.-H. (ed.). International Joint Conferences on Artificial Intelligence, p. 4976-4979 4 p. (IJCAI International Joint Conference on Artificial Intelligence).
- Unsupervised Doodling and Painting with Improved SPIRAL, Mellor, J. F. J., Park, E., Ganin, Y., Babuschkin, I., Kulkarni, T., Rosenbaum, D., Ballard, A., Weber, T., Vinyals, O. & Eslami, S. M. A., 2 Oct 2019, Machine Learning for Creativity and Design Workshop, Neural Information Processing Systems (NeurIPS).
- Attentive neural processes, Kim, H., Mnih, A., Schwarz, J., Garnelo, M., Eslami, A., Rosenbaum, D., Vinyals, O. & Teh, Y. W., 2019.
- Neural Processes, Garnelo, M., Schwarz, J., Rosenbaum, D., Viola, F., Rezende, D. J., Eslami, S. M. A. & Teh, Y. W., 4 Jul 2018, Theoretical Foundations and Applications of Deep Generative Models Workshop, International Conference on Machine Learning (ICML).
- Neural scene representation and rendering, Ali Eslami, S. M., Rezende, D. J., Besse, F., Viola, F., Morcos, A. S., Garnelo, M., Ruderman, A., Rusu, A. A., Danihelka, I., Gregor, K., Reichert, D. P., Buesing, L., Weber, T., Vinyals, O., Rosenbaum, D., Rabinowitz, N., King, H., Hillier, C., Botvinick, M. & Wierstra, D. & 2 others, , 15 Jun 2018, In: Science. 360, 6394, p. 1204-1210 7 p.
- Conditional neural processes, Gamelo, M., Rosenbaum, D., Maddison, C. J., Ramalho, T., Saxton, D., Shanahan, M., Teh, Y. W., Rezende, D. J. & Eslami, S. M. A., 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 2738-2747 10 p. (35th International Conference on Machine Learning, ICML 2018; vol. 4).
- Learning models for visual 3D localization with implicit mapping, Rosenbaum, D., Besse, F., Viola, F., Rezende, D. J. & Eslami, S. M. A., 2018, Bayesian Deep Learning workshop, Neural Information Processing Systems(NeurIPS).
- Empirical Evaluation of Neural Process Objectives, Le, T. A., Kim, H., Garnelo, M., Rosenbaum, D., Schwarz, J. & Teh, Y. W., 2018, Bayesian Deep Learning workshop, Neural Information Processing Systems (NeurIPS).
- Conditional Neural Processes, Garnelo, M., Rosenbaum, D., Maddison, C. J., Ramalho, T., Saxton, D., Shanahan, M., Teh, Y. W., Rezende, D. J. & Ali Eslami, S. M., 2018, In: Proceedings of Machine Learning Research. 80, p. 1704-1713 10 p.
- The return of the gating network: Combining generative models and discriminative training in natural image priors, Rosenbaum, D. & Weiss, Y., 2015, In: Advances in Neural Information Processing Systems. p. 2683-2691 9 p.
- Learning the local statistics of optical flow, Rosenbaum, D., Zoran, D. & Weiss, Y., 2013, In: Advances in Neural Information Processing Systems.
תחומי מחקר
- למידת מודלים של סצנות בתלת-ממד עבור הסקה הסתברותית.
- למידת ייצוגים רציפים ובדידים של אותות רציפים.
- אמורטיזציה (Amortization) של הסקה מבוססת סימולציה.
- גילוי מדעי באמצעות מידול הסתברותי גמיש של תהליך רכישת הנתונים.