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Max Planck Institute for the Physics of Complex Systems

Complex Systems, Chaos and Self-Organisation,    Information & Knowledge Management, Big Data Computing

MIAPbP - Munich Institute for Astro-, Particle and BioPhysics

Domains such as cosmology, astrophysics, nuclear or particle physics rely heavily on the use of stochastic simulation to design data analyses and perform inference with respect to fundamental physics theories. With the advances of Deep Learning, Bayesian inference techniques, a new frontier has come into view that focuses on the extension of traditional scientific programming along the two distinct directions of differentiable programming and probabilistic programming. The former plays an important role in navigating high-dimensional spaces, while the latter can manifestly incorporate generative modeling and inference into scientific data analyses. Both promise to expand the science reach of data-intensive domains through, e.g., the integration of domain knowledge and symmetries into neural networks, algorithmic robustness, alignment of science and training optimization goals, uncertainty quantification, causal inference, and more complete inference. However, most production scientific pipelines are not yet compatible with these techniques and their widespread adoption would represent a deep change in the scientific software landscape. This program will provide the opportunity for researchers from Computer Science and Fundamental Physics to develop applications as well as strategies for integrating these paradigms into existing scientific workflows and to close the gap of what is theoretically possible and practically deployed.

Computational Physics and Numerical Simulation,    High Energy Physics, Particles and Fields

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Neural Networks and Artificial Intelligence, Machine Learning,    Information & Knowledge Management, Big Data Computing

Since 2009 the Glyco-Bioinformatics Symposium aims at establishing a network of experts in glycochemistry, biology, bioinformatics and computer sciences. In addition, it provides a platform to discuss the latest outcomes presented by the MIRAGE Commission.

Unparalleled diversity and functionality of the glycome

Molecular Biology,    Genomics and Bioinformatics

MIAPbP - Munich Institute for Astro-, Particle and BioPhysics

We are happy to announce that the Differentiable and Probabilistic Programming for Fundamental Physics program includes a three day workshop. The workshop will contain talks about recent advancements in differentiable programming (DP) and probabilistic programming in the context of Physical Sciences. The workshop's diverse set of invited speakers will cover DP/ProbProg users and experts, toolmakers and authors of promising technologies. The workshop aims to explore the potential science impact of DP/ProbProg and to understand the steps towards, and challenges of, a successful implementation of these paradigms in fundamental physics.

Computational Physics and Numerical Simulation,    High Energy Physics, Particles and Fields