Credits: Mike Mackenzie

Blog Archive

Check out all blog posts in our blog archive.

22 June 2021 › Pratyush Tiwari
Can artificial intelligence help understand and predict molecular dynamics? Read More ›

25 May 2021 › Alexander Tkatchenko
On Electrons and Machine Learning Force Fields Read More ›

11 May 2021 › Chandler Squires
Predicting Gene Expression across Cell Types and Drugs Read More ›

13 April 2021 › Ferry Hooft
Discovering Collective Variables of Molecular Transitions via Genetic Algorithms and Neural Networks Read More ›

30 March 2021 › Benjamin Miller
Constrained marginal likelihood-to-evidence ratio estimation Read More ›

2 March 2021 › Jakub Tomczak
All that glitters is not Deep Learning in Life Sciences (but sometimes it is!) Read More ›

16 February 2021 › Eliu Huerta Escudero
Towards Accelerated, Reproducible, Physics-informed AI-driven Discovery Read More ›

2 February 2021 › Mario Geiger
e3nn: Euclidean symmetry for neural networks Read More ›

19 January 2021 › Dim Coumou
Machine Learning in climate science: Finding causal connections and improving seasonal forecasts Read More ›

24 November 2020 › Luisa Lucie-Smith
Machine Learning the formation of dark matter halos in the Universe Read More ›

10 November 2020 › Frank Noé
Boltzmann-generating Flows Read More ›

27 October 2020 › Gábor Csányi
Representation and regression problems for molecular structure and dynamics Read More ›

13 October 2020 › David Fischer
Attributing variance in single-cell genomics Read More ›

29 September 2020 › Christoph Weniger
Precision analysis of gravitational strong lensing images with nested likelihood-free inference Read More ›

15 September 2020 › Erik Henning Thiede
Permutation-Equivariant neural networks for Molecular Generation Read More ›

30 June 2020 › Tristan Bereau
Physically-motivated machine learning for multiscale molecular simulations Read More ›