Publications

Check out our people page to get an impression of the research done by the people at AMLab, and of course follow us on Twitter to stay tuned! Below you'll find an archive our groups output in ML research, all the way back to 1994!

2022

  1. NeurIPS
    Learning Expressive Meta-Representations with Mixture of Expert Neural Processes
    Wang, Qi, and Hoof, Herke
    In Advances in Neural Information Processing Systems 2022
  2. NeurIPS
    Factored Adaptation for Non-Stationary Reinforcement Learning
    Feng, Fan, Huang, Biwei, Zhang, Kun, and Magliacane, Sara
    In Advances in Neural Information Processing Systems 2022
  3. NeurIPS
    Neural Topological Ordering for Computation Graphs
    Gagrani, Mukul, Rainone, Corrado, Yang, Yang, Teague, Harris, Jeon, Wonseok, Hoof, Herke, Zeng, Weiliang Will, Zappi, Piero, Lott, Christopher, and Bondesan, Roberto
    In Advances in Neural Information Processing Systems 2022
  4. ICML
    Equivariant diffusion for molecule generation in 3d
    Hoogeboom, Emiel, Satorras, Vı́ctor Garcia, Vignac, Clément, and Welling, Max
    In International Conference on Machine Learning 2022
  5. ICML
    Lie Point Symmetry Data Augmentation for Neural PDE Solvers
    Brandstetter, Johannes, Welling, Max, and Worrall, Daniel E
    In International Conference on Machine Learning 2022
  6. ICML
    Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups
    Knigge, David M, Romero, David W, and Bekkers, Erik J
    International Conference on Machine Learning 2022
  7. ICML
    CITRIS: Causal Identifiability from Temporal Intervened Sequences
    Lippe, Phillip, Magliacane, Sara, Löwe, Sindy, Asano, Yuki M, Cohen, Taco, and Gavves, Efstratios
    International Conference on Machine Learning 2022
  8. ICML
    Learning Symmetric Embeddings for Equivariant World Models
    Park, Jung Yeon, Biza, Ondrej, Zhao, Linfeng, Meent, Jan-Willem, and Walters, Robin
    In International Conference on Machine Learning 2022
  9. ICML
    Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
    Antoran, Javier, Janz, David, Allingham, James Urquhart, Daxberger, Erik, Barbano, Riccardo, Nalisnick, Eric, and Hernandez-Lobato, Jose Miguel
    In Proceedings of the 39th International Conference on Machine Learning 2022
  10. ICML
    Calibrated Learning to Defer with One-vs-All Classifiers
    Verma, Rajeev, and Nalisnick, Eric
    In Proceedings of the 39th International Conference on Machine Learning 2022
  11. ICML
    Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search
    Wang, Q., and Hoof, H.
    In International Conference on Machine Learning 2022
  12. MIDL
    Experimental design for MRI by greedy policy search
    Bakker, T., Muckley, M., Romero-Soriano, A., Drozdzal, M., and Pineda, L.
    In Proceedings of Machine Learning Research Jul 2022
  13. CLeaR
    Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
    Löwe, S., Madras, D., Zemel, R., and Welling, M.
    Causal Learning and Reasoning Jul 2022
  14. ICLR
    Geometric and Physical Quantities improve E (3) Equivariant Message Passing
    Brandstetter, Johannes, Hesselink, Rob, Pol, Elise, Bekkers, Erik, and Welling, Max
    In International Conference on Learning Representations Jul 2022
  15. ICLR
    Self-Supervised Inference in State-Space Models
    Ruhe, David, and Forré, Patrick
    In International Conference on Learning Representations Jul 2022
  16. ASCOM
    Detecting dispersed radio transients in real time using convolutional neural networks
    Ruhe, David, Kuiack, Mark, Rowlinson, Antonia, Wijers, Ralph, and Forré, Patrick
    Astronomy and Computing Jul 2022
  17. ICLR
    Multi-Agent MDP Homomorphic Networks
    Pol, Elise, Hoof, Herke, Oliehoek, Frans, and Welling, Max
    In International Conference on Learning Representations Jul 2022
  18. CPAIOR
    Deep Policy Dynamic Programming for Vehicle Routing Problems
    Kool, Wouter, Hoof, Herke, Gromicho, Joaquim, and Welling, Max
    In International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research Jul 2022
  19. AAAI
    Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation
    Long, Alex, Blair, Alan, and Hoof, Herke
    In AAAI National Conference on Artificial Intelligence Jul 2022
  20. IJCAI
    Value Refinement Network (VRN)
    Wöhlke, Jan, Schmitt, Felix, and Hoof, Herke
    In International Joint Conference on Artificial Intelligence Jul 2022
  21. IJCAI
    Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods
    Höpner, Niklas, Tiddi, Ilaria, and Hoof, Herke
    In International Joint Conference on Artificial Intelligence Jul 2022

2021

  1. NeurIPS
    Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders
    Keller, T. Anderson, Gao, Qinghe, and Welling, Max
    In SVRHM 2021 Workshop at NeurIPS 2021
  2. ICCV
    Predictive Coding With Topographic Variational Autoencoders
    Keller, T. Anderson, and Welling, Max
    In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops Oct 2021
  3. NeurIPS
    Topographic VAEs learn Equivariant Capsules
    Keller, T. Anderson, and Welling, Max
    In Advances in Neural Information Processing Systems Oct 2021
  4. ICML
    Self Normalizing Flows
    Keller, T. Anderson, Peters, Jorn W.T., Jaini, Priyank, Hoogeboom, Emiel, Forré, Patrick, and Welling, Max
    In Proceedings of the 38th International Conference on Machine Learning 18–24 jul 2021
  5. NeurIPS
    As easy as APC: Leveraging self-supervised learning in the context of time series classification with varying levels of sparsity and severe class imbalance
    Wever, Fiorella, Keller, T. Anderson, Garcia, Victor, and Symul, Laura
    In Self-Supervised Learning Workshop at NeurIPS 18–24 jul 2021
  6. UAI
    Variational combinatorial sequential Monte Carlo methods for Bayesian phylogenetic inference
    Moretti, Antonio Khalil, Zhang, Liyi, Naesseth, Christian A., Venner, Hadiah, Blei, David, and Pe’er, Itsik
    In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence 27–30 jul 2021
  7. AISTATS
    Rate-Regularization and Generalization in Variational Autoencoders
    Bozkurt, Alican, Esmaeili, Babak, Tristan, Jean-Baptiste, Brooks, Dana, Dy, Jennifer, and Meent, Jan-Willem
    In International Conference on Artificial Intelligence and Statistics Mar 2021
  8. NeurIPS
    Nested Variational Inference
    Zimmermann, Heiko, Wu, Hao, Esmaeili, Babak, and Meent, Jan-Willem
    In Advances in Neural Information Processing Systems Mar 2021
  9. ICML
    Conjugate Energy-Based Models
    Wu, Hao*, Esmaeili, Babak*, Wick, Michael, Tristan, Jean-Baptiste, and van de Meent, Jan-Willem
    In Proceedings of the 38th International Conference on Machine Learning (ICML) 18–24 jul 2021
  10. UAI
    Learning proposals for probabilistic programs with inference combinators
    Stites, Sam, Zimmermann, Heiko, Wu, Hao, Sennesh, Eli, and Meent, Jan-Willem
    In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence 27–30 jul 2021
  11. AISTATS
    Predictive Complexity Priors
    Nalisnick, Eric, Gordon, Jonathan, and Miguel Hernandez-Lobato, Jose
    In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics 13–15 apr 2021
  12. ICML
    Bayesian Deep Learning via Subnetwork Inference
    Daxberger, Erik, Nalisnick, Eric, Allingham, James U, Antoran, Javier, and Hernandez-Lobato, Jose Miguel
    In Proceedings of the 38th International Conference on Machine Learning 18–24 jul 2021
  13. JMLR
    Normalizing Flows for Probabilistic Modeling and Inference
    Papamakarios, George, Nalisnick, Eric, Rezende, Danilo Jimenez, Mohamed, Shakir, and Lakshminarayanan, Balaji
    Journal of Machine Learning Research 18–24 jul 2021
  14. JMS
    Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator
    Wang, Shihan, Zhang, Chao, Kröse, Ben, and Hoof, Herke
    Journal of Medical Systems 18–24 jul 2021
  15. IJERPH
    Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study
    Wang, S., Sporrel, K., Hoof, H., Simons, M., Boer, R., Ettema, D., Nibbeling, N., Deutekom, M., and Kröse, B.
    International Journal of Environmental Research and Public Health, Special Issue 18–24 jul 2021
  16. ICRA
    Hierarchies of Planning and Reinforcement Learning for Robot Navigation
    Wöhlke, J., Schmitt, F., and Hoof, H.
    In IEEE International Conference on Robotics and Automation 18–24 jul 2021
  17. ICML
    Deep Coherent Exploration For Continuous Control
    Zhang, Yijie, and Hoof, Herke
    In International Conference on Machine Learning 18–24 jul 2021
  18. UrbComp
    Back to Basics: Deep Reinforcement Learning in Traffic Signal Control
    Kanis, S., Samson, L., Bloembergen, D., and Bakker, T.
    The 10th International Workshop on Urban Computing Nov 2021

All Publications (via Pure)