Sebastian Nilsson

Machine Learning Engineer working with Knowledge Graphs for Drug Discovery at @AstraZeneca. Interested in creating trustworthy, efficient and interpretable ML

[Bojan Tunguz @tunguz]

10,000 GPUs is all you need.

[memenetes @memenetes]

Watching the devs using Kubernetes

[Nature Communications @NatureComms]

.@useless_ulysses @elipapa @KrishnaCBulusu @michaelughetto @dpolychr2 @lostinromsey @drysci @M_Pfiver develop a recommender system ranking genes based on trade-offs between diverse types of evidence linking them to potential mechanisms of EGFRi resistance
https://t.co/AZDqNBlMPy

[PyTorch @PyTorch]

ChemicalX is a PyTorch and TorchDrug based #deeplearning library for drug pair scoring which predicts drug interactions, polypharmacy side effects and possible synergies, in both a biological and chemical context. Learn more at: https://t.co/5Vsn1ykXxA

[MLoG Workshop @MLoG_Workshop]

One of the great papers that we will feature at MLoG is "Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs"! https://t.co/uvlJ6cY03i

A fantastic explainability method applied to drug discovery!
=> impressive and impactful results

[Philip Vollet @philipvollet]

Awesome Explainable Graph Reasoning! A collection of research papers and software related to explainability in graph machine learning.

@benrozemberczki

Don't forget to spend some star love for the repository!

https://t.co/M4282JDZm7

[Real Python @realpython]

RexMex: Recommender System Evaluation Library #python https://t.co/sg28HTiWWP

[NVIDIA AI @NVIDIAAI]

At #GTC21, @michaelughetto and @sebastiandro from @AstraZeneca will discuss how they've integrated @rapidsai, and in particular cuGraph, in multiple stages of the data life cycle. Add the session to your @nvidiagtc schedule: https://t.co/7ujdqVS2kE

[Daniel Probst @[email protected] @skepteis]

Neat infographic: Lifesaving innovations.

[Gav Edwards 🤖 @gav_eddy]

Fantastic work and presentation by @useless_ulysses 👏 Using knowledge graphs for drug discovery recommendations 💊 #RecSys2021

[Matthias Samwald @matthiassamwald]

Join our ML challenge on biomedical link prediction and explainable AI! Prizes to win:
500 € for best performing model
500 € for most explainable model

https://t.co/vLKuxMj8q9

[eliseo papa @elipapa]

do you know #MachineLearning and would like to apply to a #biology problem?
There are some basics concepts you need to know first.
We have started a list of our favourite links https://t.co/QVS4VwXcSL including links to a great article by @jsomers, courses by @UriAlonWeizmann