The path to PhD - Advice from a young scientist
I am Scientist ยท Episode
I had the pleasure of being interviewed on the @i-am-scientist.bsky.social podcast by @lisaschmors.bsky.social and @philipphubert.bsky.social . I talk about how I ended up writing my newsletter (path2phd.substack.com) and the people who supported me all along. Enjoy!
02.05.2025 17:12 โ ๐ 4 ๐ 1 ๐ฌ 0 ๐ 1
Soโdoes this mean theory is doomed, and AI engineering is just a random walk? Not at all!
๐ก @rpatrik96.bsky.social @wielandbrendel.bsky.social Randall Balestriero did an amazing job clarifying where theory can help practiceโand where practice should inspire theory.
๐ค
18.04.2025 14:15 โ ๐ 1 ๐ 1 ๐ฌ 1 ๐ 0
Kudos to the great team @ninamiolane.bsky.social @rpatrik96.bsky.social @charlesoneill.bsky.social Harald Maurer ๐
04.03.2025 19:43 โ ๐ 6 ๐ 3 ๐ฌ 0 ๐ 0
How can neural nets extract *interpretable* features from dataโ& uncover new science?
๐ Discover our mathematical framework tackling this question w/ identifiability theory, compressed sensing, interpretability & geometry!๐
By @david-klindt.bsky.social @rpatrik96.bsky.social C. O'Neill H Maurer
05.03.2025 14:41 โ ๐ 18 ๐ 8 ๐ฌ 0 ๐ 1
New preprint!๐
Decoding neural representations is a challenge in neuroscience & AI.
๐ Learn how identifiability theory, compressed sensing & interpretability research -w/ a dash of geometry- can help!
@david-klindt.bsky.social @rpatrik96.bsky.social C. O'Neill H. Maurer @ninamiolane.bsky.social
05.03.2025 14:43 โ ๐ 8 ๐ 4 ๐ฌ 0 ๐ 0
Hiring announcement: ELLIS Institute Tรผbingen is looking for ML Researchers & Engineers for Open-Source AI Tutoring (m/f/d). The image features a white background with bold black text and the colorful ELLIS logo at the bottom.
๐ Weโre hiring! Join Bernhard Schรถlkopf & me at @ellisinsttue.bsky.social to push the frontier of #AI in education!
Weโre building cutting-edge, open-source AI tutoring models for high-quality, adaptive learning for all pupils with support from the Hector Foundation.
๐ forms.gle/sxvXbJhZSccr...
11.02.2025 16:34 โ ๐ 8 ๐ 14 ๐ฌ 1 ๐ 1
NeurIPS Poster Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD PromptsNeurIPS 2024
Check out our @neuripsconf.bsky.social spotlight on showing how language models learn to extrapolate and compose language rules.
See you on Fri 13 Dec 4:30 p.m. PST โ 7:30 p.m. PST at poster #2702 in East Hall.
neurips.cc/virtual/2024...
13.12.2024 16:59 โ ๐ 0 ๐ 0 ๐ฌ 0 ๐ 0
ELLIS PhD Award 2024 in text and three photos of the winners, then the ELLIS logo at the bottom
Congrats to the recipients of the 2024 ELLIS PhD Award!
Co-winners: @koloskova.bsky.social (efficiency in decentralized learning) & Luigi Gresele (identifiable representation learning)
Runner up: @schwarzjn.bsky.social (sparse parameterizations)
Read more about them: bit.ly/4fg4jkg
#AI #ML
12.12.2024 08:46 โ ๐ 42 ๐ 5 ๐ฌ 1 ๐ 2
1/ Hi all, I am at #NeurIPS2024 and I will be hiring a postdoc in probabilistic machine learning starting asap.
Research interests: amortized, approximate & simulator-based inference, Bayesian optimization, and AI4science.
Get in touch for a chat or come to our posters today 11AM or Friday 11AM!
11.12.2024 16:26 โ ๐ 25 ๐ 11 ๐ฌ 1 ๐ 1
How to Merge Your Multimodal Models Over Time?
Model merging combines multiple expert models - finetuned from a base foundation model on diverse tasks and domains - into a single, more capable model. However, most existing model merging approaches...
๐ New Paper: "How to Merge Your Multimodal Models Over Time?"
arxiv.org/abs/2412.06712
Model merging assumes all finetuned models are available at once. But what if they need to be created over time?
We study Temporal Model Merging through the TIME framework to find out!
๐งต
11.12.2024 18:00 โ ๐ 24 ๐ 7 ๐ฌ 1 ๐ 2
Research Assistant/Associate in Machine Learning (Fixed Term) - Job Opportunities - University of Cambridge
Research Assistant/Associate in Machine Learning (Fixed Term) in the Department of Engineering at the University of Cambridge.
We are looking for a PostDoc on human-AI interaction to work with @mirizilka.bsky.social
The project studies systems used in law enforcement or legal decision-making, when humans act on recommendations/predictions made by ML algorithms.
Email for details.
www.jobs.cam.ac.uk/job/49538/
11.12.2024 20:16 โ ๐ 7 ๐ 2 ๐ฌ 0 ๐ 1
Check out our
@neuripsconf.bsky.social
spotlight on showing a useful inductive bias in language models to extrapolate language rules.
See you on Fri 13 Dec 4:30 p.m. PST โ 7:30 p.m. PST at poster #2702.
06.12.2024 18:47 โ ๐ 3 ๐ 0 ๐ฌ 0 ๐ 0
Next week I will be in Berkeley. Reach out if you'd like to talk about OOD/compositional generalization, causality, SSL, or inductive biases.
28.11.2024 07:26 โ ๐ 1 ๐ 0 ๐ฌ 0 ๐ 0
The โจML Internship Feedโจ is here!
@serge.belongie.com and I created this feed to compile internship opportunities in AI, ML, CV, NLP, and related areas.
The feed is rule-based. Please help us improve the rules by sharing feedback ๐งก
๐ Link to the feed: bsky.app/profile/did:...
22.11.2024 21:46 โ ๐ 63 ๐ 16 ๐ฌ 7 ๐ 1
Poster of the EIPOD call
Join the Interdisciplinary Postdoc Fellowship Program at the European Molecular Biology Laboratory (EMBL), one of the best places to do research in modern biology and develop your career.
Great opportunities for statisticians, comp. biologists, AI experts, mathem. modelers!
www.embl.org/eipod-linc
22.11.2024 09:02 โ ๐ 41 ๐ 32 ๐ฌ 0 ๐ 0
Machine Learning Researcher and Social Entrepreneur | Group Leader at ELLIS Institute Tรผbingen & Max Planck Institute for Intelligent Systems robustml.is.mpg.de | Co-Founder maddox.ai | Co-Initiator bw-ki.de | @ellis.eu scholar
Professor, Santa Fe Institute. Research on AI, cognitive science, and complex systems.
Website: https://melaniemitchell.me
Substack: https://aiguide.substack.com/
Machine Learning PhD student at Cambridge University, visiting Cornell. Previously at Oxford and Google. Principled ML & applications in medicine.
Deep learner at FAIR. Into codegen, RL, equivariance, generative models. Spent time at Qualcomm, Scyfer (acquired), UvA, Deepmind, OpenAI.
Secular Bayesian.
Professor of Machine Learning at Cambridge Computer Lab
Talent aficionado at http://airetreat.org
Alum of Twitter, Magic Pony and Balderton Capital
โต๏ธ Research Resident @ Midjourney
๐ช๐บ Member @ellis.eu
๐ค Generative NNs, Deep Learning, ProbML, Simulation Intelligence
๐ PhD+MSc Computer Science, MSc Psychology
๐ก https://marvin-schmitt.com
DeepMind Professor of AI @Oxford
Scientific Director @Aithyra
Chief Scientist @VantAI
ML Lead @ProjectCETI
geometric deep learning, graph neural networks, generative models, molecular design, proteins, bio AI, ๐ ๐ถ
Full Professor of Computational Statistics at TU Dortmund University
Scientist | Statistician | Bayesian | Author of brms | Member of the Stan and BayesFlow development teams
Website: https://paulbuerkner.com
Opinions are my own
Professor in computational Bayesian modeling at Aalto University, Finland. Bayesian Data Analysis 3rd ed, Regression and Other Stories, and Active Statistics co-author. #mcmc_stan and #arviz developer.
Web page https://users.aalto.fi/~ave/
AI for Science, deep generative models, inverse problems. Professor of AI and deep learning @universitedeliege.bsky.social. Previously @CERN, @nyuniversity. https://glouppe.github.io
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him
๐ https://april-tools.github.io
Professor of Statistics and Machine Learning at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
Full Professor at @deptmathgothenburg.bsky.social | simulation-based inference | Bayes | stochastic dynamical systems | https://umbertopicchini.github.io/
Associate Professor of Machine Learning, University of Oxford;
OATML Group Leader;
Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
Assistant Professor of Machine Learning
Generative AI, Uncertainty Quantification, AI4Science
Amsterdam Machine Learning Lab, University of Amsterdam
https://naesseth.github.io
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
Associate Prof | AI for drug discovery | Eindhoven University of Technology | Previously ETH Zurich & UniMiB | she/her ๐ณ๏ธโ๐
Speech โข Language โข Learning
https://grzegorz.chrupala.me
@ Tilburg University
Faculty at CWI & ELLIS Amsterdam https://trl-lab.github.io. Prev at UC Berkeley and the University of Amsterdam. Research on AI and tabular data to democratize insights from structured data.
https://www.madelonhulsebos.com