no code implementations • 15 Nov 2022 • Seth D. Axen, Alexandra Gessner, Christian Sommer, Nils Weitzel, Álvaro Tejero-Cantero
Paleoclimatology -- the study of past climate -- is relevant beyond climate science itself, such as in archaeology and anthropology for understanding past human dispersal.
1 code implementation • 3 Dec 2021 • Jonathan Wenger, Nicholas Krämer, Marvin Pförtner, Jonathan Schmidt, Nathanael Bosch, Nina Effenberger, Johannes Zenn, Alexandra Gessner, Toni Karvonen, François-Xavier Briol, Maren Mahsereci, Philipp Hennig
Probabilistic numerical methods (PNMs) solve numerical problems via probabilistic inference.
1 code implementation • 15 Feb 2021 • Filip de Roos, Alexandra Gessner, Philipp Hennig
Although it is widely known that Gaussian processes can be conditioned on observations of the gradient, this functionality is of limited use due to the prohibitive computational cost of $\mathcal{O}(N^3 D^3)$ in data points $N$ and dimension $D$.
1 code implementation • 12 Feb 2021 • Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Riemannian manifolds provide a principled way to model nonlinear geometric structure inherent in data.
2 code implementations • 21 Oct 2019 • Alexandra Gessner, Oindrila Kanjilal, Philipp Hennig
Integrals of linearly constrained multivariate Gaussian densities are a frequent problem in machine learning and statistics, arising in tasks like generalized linear models and Bayesian optimization.
no code implementations • 27 Mar 2019 • Alexandra Gessner, Javier Gonzalez, Maren Mahsereci
Bayesian quadrature (BQ) is a sample-efficient probabilistic numerical method to solve integrals of expensive-to-evaluate black-box functions, yet so far, active BQ learning schemes focus merely on the integrand itself as information source, and do not allow for information transfer from cheaper, related functions.