Publications
T. Anderson Keller, Lyle Muller, Terrence Sejnowski, Max Welling. Traveling Waves Encode the Recent Past and Enhance Sequence Learning. International Conference on Learning Representations (ICLR), 2024.
Metod Jazbec, James U. Allingham, Dan Zhang, Eric Nalisnick. Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity. Advances in Neural Information Processing Systems (NeurIPS), 2023.
Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling. Flow Factorized Representation Learning. Advances in Neural Information Processing Systems (NeurIPS), 2023.
T. Anderson Keller, Max Welling. Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks. International Conference on Machine Learning (ICML), 2023.
Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling. Latent Traversals in Generative Models as Potential Flows. International Conference on Machine Learning (ICML), 2023.
Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling. Complex-Valued Autoencoders for Object Discovery. Transactions on Machine Learning Research (TMLR), 2022.
Artem Moskalev, Anna Sepliarskaia, Ivan Sosnovik, Arnold Smeulders. LieGG: Studying Learned Lie Group Generators. Advances in Neural Information Processing Systems (NeurIPS), 2022.
Artem Moskalev, Ivan Sosnovik, Volker Fisher, Arnold Smeulders. Contrasting Quadratic Assignments for Set-Based Representation Learning. European Conference on Computer Vision (ECCV), 2022.
Sindy Löwe, David Madras, Richard Zemel, Max Welling. Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data. Causal Learning and Reasoning (CLeaR), 2022.