Updated 10 months ago

https://github.com/astarvienna/irdb • Science 26%

A database containing instrument data for infrared telescopes

Updated 10 months ago

https://github.com/astarvienna/metiswise • Science 26%

MetisWISE is the software for the METIS AIT Archive

Updated 10 months ago

https://github.com/astarvienna/anisocado • Science 26%

A package to generate off-axis PSFs for the SCAO mode for MICADO at the ELT

Updated 10 months ago

https://github.com/astarvienna/metis_drld • Science 26%

A normal git remote for https://www.overleaf.com/project/5f1abb4137d7690001f8aeb1 , not an export

Updated 10 months ago

https://github.com/astcherbinine/aspy • Science 13%

Personnal additions to Python

Updated 10 months ago

https://github.com/astorfi/camel • Science 10%

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

Updated 10 months ago

https://github.com/astorfi/adversarial-model-inversion • Science 23%

Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)

Updated 10 months ago

https://github.com/astrazeneca/multimodal-python-course • Science 49%

The purpose of the code is to facilitate a comprehensive understanding of multimodal data science applications within medical domain. The code serves to support the delivery of a cutting-edge workshop designed to introduce researchers to the rapidly evolving field of multimodal data science

Updated 10 months ago

https://github.com/astrazeneca/qsuse • Science 13%

R library that provides an import mechanism like python to import local source files. It is not meant to replace library(), or doublecolon:: prefixing

Updated 10 months ago

https://github.com/astrazeneca/agpower • Science 26%

agpower: Recurrent event analysis planning using the Andersen-Gill model in R

Updated 10 months ago

https://github.com/astrazeneca/ibd-interpret • Science 26%

We trained high performing open source models on image scans of tissue biopsies to predict endoscopic categories in inflammatory bowel disease. These predictive models can help us better understand the disease pathology and represent a step towards automated clinical recruitment strategies.