Jannis Born

354 posts

Jannis Born banner
Jannis Born

Jannis Born

@JannisBorn

Left X, find me on Bluesky: https://t.co/fz5QWs5ugO

Zürich, Schweiz Katılım Aralık 2016
368 Takip Edilen659 Takipçiler
Sabitlenmiş Tweet
Jannis Born
Jannis Born@JannisBorn·
I am leaving X in favor of BlueSky. Since Elon took over, X departed from Twitter's values and turned into a dystopian platform. I have three two main reasons: (1) Zero content moderation is unacceptable. (2) Right-wing content skyrocketed. Details in the 🧵⬇️
English
1
0
4
189
Jannis Born
Jannis Born@JannisBorn·
(2) Right-wing content skyrocketed. This was strategic due to the 2024 presidential election. All users were at the mercy of Elon's personal interests. If that is not the definition of dystopia, what is? There is ample evidence for this: pewresearch.org/internet/2024/…
English
0
0
1
68
Jannis Born
Jannis Born@JannisBorn·
(1) Social media platforms have responsibilities akin to journalistic formats. They dont *generate* fake news, but they should be accountable if they flush it to my newsfeed. If the NYT had a fake news headline, the publisher would resign. Listen to Harari bit.ly/4ggSZWd
English
1
0
1
108
Jannis Born
Jannis Born@JannisBorn·
I am leaving X in favor of BlueSky. Since Elon took over, X departed from Twitter's values and turned into a dystopian platform. I have three two main reasons: (1) Zero content moderation is unacceptable. (2) Right-wing content skyrocketed. Details in the 🧵⬇️
English
1
0
4
189
Jannis Born retweetledi
Nikita Janakarajan
Nikita Janakarajan@niklexical·
📖Book Chapter Alert! “Language Models in Molecular Discovery” (link.springer.com/chapter/10.100…) is a deep dive into how language models can be used to accelerate molecular discovery, highlighting their strengths and weaknesses.
English
2
2
14
1K
Jannis Born
Jannis Born@JannisBorn·
@Pseudomanifold @unifr Congrats Bastian and welcome back to Switzerland! Incredibly deserved! 💪🚀Even more great research ahead for you 🤩
English
1
0
2
49
Bastian Grossenbacher-Rieck
Bastian Grossenbacher-Rieck@Pseudomanifold·
Friends, I am beyond happy! I'm starting a new position as Full Professor of #MachineLearning at the University of Fribourg @unifr 🇨🇭! With #SwissAI and many other initiatives, I am taking my research at the intersection of #geometry, #topology, and #MachineLearning to a new level 🚀. This #SwissNationalDay will thus hold an even more special meaning for me—thanks for this wonderful chance, my dear confederates! The past few years have been a veritable roller coaster 🎢, with ups and downs. Through it all, I was sustained and supported by my family, for which I am eternally grateful. As much as we like to believe it in academia, 'no man is an island,' and I have tons of people to thank, foremost among them my postdoctoral adviser @kmborgwardt, as well as my long-term collaborators @KrishnaswamyLab and @mrguywolf. I am also indebted to my great research group at the AIDOS Lab. Working with all of you is a pleasure! 🙏 Finally, I am grateful for the advice of my mentors and role models @stefanabauer, @mmbronstein, and @guennemann (plus many others—you know who you are). It's time to give back now and make academia better! PS: 🔥I'm hiring soon! 🔥Please share widely and direct any inquiries to my e-mail or DM.
English
80
37
542
37.9K
Jannis Born
Jannis Born@JannisBorn·
Our ICML paper: ML + quantum computing + optimal transport = 🚀! Learn distributions conditionally with quantum. Including a 24-qubit hardware run on the assignment problem (predicting doubly-stochastic matrices) @IBMResearch 📖 ibm.biz/qontot-icml 📹 ibm.biz/qontot-yt
English
1
13
35
2.4K
Jannis Born
Jannis Born@JannisBorn·
Consider these fantastic opportunities in #Lausanne if you're into ML for Biomedicine and are looking for a PhD, PostDoc or master thesis! I can speak from experience and it has been super inspiring to work with @marianna_raps!
Marianna Rapsomaniki@marianna_raps

📢 We are hiring! 📢 Are you a MSc/PhD👩‍🎓👨‍🎓 passionate about #AI #ML in #cancer, looking for your next career step? Join our newly-founded AI/ML for Biomedicine group part of the Biomedical Data Science Center at @unil and @CHUVLausanne in beautiful Lausanne!🇨🇭🏔🌈 👇

English
2
3
9
1.6K
Jannis Born
Jannis Born@JannisBorn·
In our new paper in @Nature_NPJ we propose to use **z-scored** drug response measures (IC50, AUC etc). We show that conventional metrics hamper the development of personalized prediction models 🤯 Thanks to all collaborators!
npj Journals@Nature_NPJ

New in #npjPrecisionOncology: Drug response models overlook nuances of drug effects between cancer subtypes. The solution? Use z-scored measures to unlock more personalized drug response predictions @jannisborn @MariannKruithof @Katja_HB4 @PChouvardas bit.ly/4biMxLS

English
0
0
16
472
Jannis Born retweetledi
Marvin Alberts
Marvin Alberts@malberts99·
Interested in Uncertainty Quantification for Sequence Prediction? Come check out our poster at @RealAAAI today. We add rigorous uncertainty quantification to Beam Search using Conformal Predictions! @nickgermann @IBMResearch
Marvin Alberts tweet media
English
1
12
26
2K
Jannis Born retweetledi
Oliver Schilter
Oliver Schilter@OSchilter·
Introducing Clipboard-to-SMILES Converter: a macOS app for effortless conversion of screenshots into molecular structures (SMILES, SELFIES, etc.) right from your clipboard, complete with a convenient history feature! Check out our paper and download it: doi.org/10.1002/ail2.91
English
6
60
271
22K
Jannis Born retweetledi
Marianna Rapsomaniki
Marianna Rapsomaniki@marianna_raps·
Join our Track on #AI for #drugdiscovery at #AMLD2024 March 25 in Lausanne 🇨🇭! 🔥 Sessions on #AI for #molecules, #singlecell #omics 🔊 Stellar invited talks from @mo_lotfollahi @fra_grisoni and @DRoqueiro 🗒️ Submit your abstract and get selected for a short talk or a poster 👇
AMLD Intelligence Summit@appliedmldays

The call for Posters is now open for AMLD EPFL 2024! Passionate about AI and machine learning? Join a track at AMLD EPFL 2024! Find out more here. go.epfl.ch/AMLDTracks Early Bird rates until 25 January. Register now! go.epfl.ch/AMLD #AMLDEPFL2024 #AI #MachineLearning

English
2
3
12
5.5K
Jannis Born retweetledi
Robert Palgrave
Robert Palgrave@Robert_Palgrave·
We have now completed our analysis of new materials reported in the Google Deepmind / Berkeley autonomous lab paper. My own initial analysis is in the quote tweet. Happy to have worked with @SchoopLab to jointly put together a comprehensive analysis, now available on @ChemRxiv. This thread is my personal view after having looked at the detail of each of the materials reported 🧵 chemrxiv.org/engage/chemrxi…
Robert Palgrave@Robert_Palgrave

This exciting paper shows AI design of materials, robotic synthesis. 10s of new compounds in 17 days. But did they? This paper has very serious problems in materials characterisation. In my view it should never have got near publication. Hold on tight let's take a look 😱

English
18
184
848
514.7K
Jannis Born retweetledi
Mara Graziani
Mara Graziani@mormontre·
Entering 2024 as a Research Scientist at @IBMResearch Europe💃 thrilled to join a team of pure🔥 and to finally be a full member of the crew. Looking forward to the great things coming ahead 🤓
English
10
3
98
17.2K
Jannis Born retweetledi
Nicolas Deutschmann
Nicolas Deutschmann@nickgermann·
Our paper got accepted at #AAAI24! 🎉 We propose two new sequence generation algorithms with "error bars", by adapting beam search to conformal predictions. If you use LLMs for science, like predicting molecules or proteins that verify some conditions, check it out!
Nicolas Deutschmann@nickgermann

Here's our preprint on conformal sequence generation! w/ @malberts99 @MariaRoCompBio arxiv.org/abs/2309.03797 Two new algorithms for sequence prediction sets with guarantees: - Conformal sub-beams: pruning standard beams - Conformal dynamic beams: step-by-step conformal decoding.

English
0
8
25
3.3K
Jannis Born
Jannis Born@JannisBorn·
4/4 “Characterizing pre-trained and task-adapted molecular representations” — #UniReps workshop (Friday) TL;DR:  A post-hoc quality evaluation method for representation learning models and domain adaptation methods that is task and modality-agnostic
English
0
2
5
719
Jannis Born
Jannis Born@JannisBorn·
3/4 “Language Models in Molecular Discovery” — AI4Science workshop (Saturday, brought to you by @niklexical) TL;DR: How to leverage language models to accelerate molecular discovery, despite their limitations.
English
1
3
5
837
Jannis Born
Jannis Born@JannisBorn·
We're in 2nd half of #NeurIPS2023, but still much exciting research ahead!Thrilled to present some work from #AI4SD team @IBMResearch. Topics cover quantum computing, foundation models, optimal transport, digitization of lab workflows, language models in molecular design & more⬇️
English
1
7
21
1.5K