2024
- Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
- Fast and Reliable Probabilistic Reflectometry Inversion with Prior-Amortized Neural Posterior Estimation
- Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge
- Frequency effects in linear discriminative learning
- Predictive, scalable and interpretable knowledge tracing on structured domains
T Freiesleben, G König, C Molnar, Á Tejero-Cantero
Minds & Machines 34, 32 (2024)
V Starostin, M Dax, A Gerlach, A Hinderhofer, Á Tejero-Cantero, F Schreiber
Submitted
V Munteanu, V Starostin, A Greco, L Pithan, A Gerlach, A Hinderhofer, S Kowarik, F Schreiber
Journal of Applied Crystallography 57, 456-469 (2024)
Cluster research highlight (release july 2024)
M Heitmeier, YY Chuang, SD Axen, RH Baayen
Frontiers in Human Neuroscience 17, 1242720 (2024)
H Zhou, R Bamler, C M Wu, Á Tejero-Cantero
International Conference on Learning Representations (ICLR), 2024
paper, repo, mlcolab blog post
Cluster research highlight (released june 2024)
2023
- Manifolds.jl: an extensible Julia framework for data analysis on manifolds
- Efficiently generating inverse-Wishart matrices and their Cholesky factors
- BridgeStan: Efficient in-memory access to the methods of a Stan model
- The Dynamic and Structured Nature of Learning and Memory
SD Axen, M Baran, R Bergmann, K Rzecki
ACM Transactions on Mathematical Software 49, 1–23 (2023)
arXiv 2023
EA Roualdes, B Ward, B Carpenter, A Seyboldt, SD Axen
Journal of Open Source Software 8, 5236 (2023)
H Zhou, C Wu, Á Tejero-Cantero
Conference on Cognitive Computational Neuroscience (2023)
2022
- Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes
- GATSBI: Generative adversarial training for simulation-based inference
SD Axen, A Gessner, C Sommer, N Weitzel, Á Tejero-Cantero
NeurIPS 2022 workshop paper
Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Á Tejero-Cantero, David S Greenberg, Pedro J Gonçalves, Jakob H Macke
International Conference on Learning Representations, ICLR (2022)