@smaglia.bsky.social
Assistant prof in the Amsterdam Machine Learning Lab at the University of Amsterdam | ELLIS scholar | #causality #causalML anything #causal | 🇮🇹🇸🇮 in 🇳🇱 | #UAI2025 program chair https://saramagliacane.github.io/
@alxndrmlk.bsky.social
"The Causal Guy" http://causalpython.io Author || Advisor || Educator Host at http://CausalBanditsPodcast.com Causal ML Tutor @ Uni of Oxford CausalSky: https://bsky.app/profile/did:plc:imz3rf35poonl7yxt7bogui4/feed/aaamrclcu3tfa
@ian-goodfellow.bsky.social
Research Scientist at DeepMind. Opinions my own. Inventor of GANs. Lead author of http://www.deeplearningbook.org . Chronically ill: bilateral Ménière’s disease + long COVID. Founding chairman of www.publichealthactionnetwork.org
@iclr-conf.bsky.social
International Conference on Learning Representations https://iclr.cc/
@dennisfrauen.bsky.social
(Ellis) PhD student at LMU Munich. Interested in causal machine learning and reinforcement learning
@davidruegamer.bsky.social
Associate Prof @ LMU Munich PI @ Munich Center for Machine Learning Ellis Member Associate Fellow @ relAI ----- https://davidruegamer.github.io/ | https://www.muniq.ai/ ----- BNNs, UQ in DL, DL theory (Overparam, Implicit Bias, Optim), Sparsity
@tfjgeorge.bsky.social
Explainability of deep neural nets and causality https://tfjgeorge.github.io/
@vidhishab.bsky.social
AI Evaluation and Interpretability @MicrosoftResearch, Prev PhD @CMU.
@tmiller-uq.bsky.social
Professor in Artificial Intelligence, The University of Queensland, Australia Human-Centred AI, Decision support, Human-agent interaction, Explainable AI https://uqtmiller.github.io
@berkustun.bsky.social
Assistant Prof at UCSD. I work on interpretability, fairness, and safety in ML. www.berkustun.com
@hildekuehne.bsky.social
Professor for CS at the Tuebingen AI Center and affiliated Professor at MIT-IBM Watson AI lab - Multimodal learning and video understanding - GC for ICCV 2025 - https://hildekuehne.github.io/
@arxiv-stat-ml.bsky.social
source: https://arxiv.org/rss/stat.ML maintainer: @tmaehara.bsky.social
@hiddefokkema.bsky.social
PhD candidate in Mathematical Machine Learning with @tverven | Researching formal XAI | Maths nerd | Occasional producer of electronic music https://www.hidde-fokkema.com
@teorth.bsky.social
Mathematician at UCLA. My primary social media account is https://mathstodon.xyz/@tao . I also have a blog at https://terrytao.wordpress.com/ and a home page at https://www.math.ucla.edu/~tao/
@beenwrekt.bsky.social
Blog: https://argmin.substack.com/ Webpage: https://people.eecs.berkeley.edu/~brecht/
@pseudomanifold.topology.rocks
Dad · Geometry ∩ Topology ∩ Machine Learning Professor at University of Fribourg While #geometry & #topology may not save the world, they may well save something that is homotopy-equivalent to it. 🏠 https://bastian.rieck.me/ 🏫 https://aidos.group
@larsweisbrod.det.social.ap.brid.gy
The days are long but the years are short DIE ZEIT Feuilleton https://linktr.ee/larsweisbrod [bridged from @larsweisbrod@det.social by Bridgy Fed]
@blog.neurips.cc.web.brid.gy
[bridged from https://blog.neurips.cc/ on the web: https://fed.brid.gy/web/blog.neurips.cc ]
@valik-melnychuk.bsky.social
PhD Candidate at Institute of AI in Management, LMU Munich causal machine learning, causal inference
@mcknaus.bsky.social
Assistant Professor of "Data Science in Economics" at Uni Tübingen. Interested in the intersection of causal inference and so-called machine learning. Teaching material: https://github.com/MCKnaus/causalML-teaching Homepage: mcknaus.github.io
@ribana.bsky.social
Professor of Data Science for Crop Systems at Forschungszentrum Jülich and University of Bonn Working on Explainable ML🔍, Data-centric ML🐿️, Sustainable Agriculture🌾, Earth Observation Data Analysis🌍, and more...
@causalab.bsky.social
Actionable #causalinference with real-world impact. We use health data to help decision makers make better decisions. We train investigators at Harvard T.H. Chan School of Public Health. Connect with CAUSALab: https://linktr.ee/causalab
@causalscience.org
Fostering a dialogue between industry and academia on causal data science. Causal Data Science Meeting 2024: causalscience.org
@lizstuart.bsky.social
Statistician; Professor and Chair @JHUBiostat @JohnsHopkinsSPH, w/links to @SREESociety, @AmericanHealth. Oh, & spouse, mom, runner, traveler.
@miguelhernan.org
https://miguelhernan.org/ Using health data to learn what works. Making #causalinference less casual. Director, @causalab.bsky.social Professor, @hsph.harvard.edu Methods Editor, Annals of Internal Medicine @annalsofim.bsky.social
@apepa.bsky.social
Assistant Professor, University of Copenhagen; interpretability, xAI, factuality, accountability, xAI diagnostics https://apepa.github.io/
@christophmolnar.bsky.social
Author of Interpretable Machine Learning and other books Newsletter: https://mindfulmodeler.substack.com/ Website: https://christophmolnar.com/
@amirhkarimi.bsky.social
🇮🇷 🇨🇦 👨🏻🏫 Asst Prof of ML @UWaterloo & Faculty Affiliate @VectorInst 🔎 Explainable AI, Human-AI Teams 🧠🤖 ex-{@DeepMind, @GoogleAI, @Meta} CHARM Lab👇
@diatkinson.bsky.social
PhD student at Northeastern, previously at EpochAI. Doing AI interpretability. diatkinson.github.io
@colah.bsky.social
Reverse engineering neural networks at Anthropic. Previously Distill, OpenAI, Google Brain.Personal account.
@swetakar.bsky.social
Machine learning PhD student @ Blei Lab in Columbia University Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling! Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams. 🔗 www.sweta.dev
@joestacey.bsky.social
NLP PhD student at Imperial College London and Apple AI/ML Scholar. My research is on model robustness and interpretability. #NLP #NLProc
@clemensstachl.bsky.social
Associate Prof. of Behavioral Science and Director of the IBT @HSGStGallen #mobilesensing, #dailybehavior, #personality, #machinelearning, #explainableAI
@rpatrik96.bsky.social
PhD student working on understanding why neural nets generalize @MPI Tübingen | ex-Vector | path2phd.substack.com | 🇭🇺 🇪🇺
@dziadzio.bsky.social
ELLIS PhD student in machine learning at IMPRS-IS. Continual learning at scale. sebastiandziadzio.com
@ml4science.bsky.social
Cluster of Excellence "Machine Learning: New Perspectives for Science" at University of Tübingen, Germany. Blog: https://www.machinelearningforscience.de/
@mohaas.bsky.social
IMPRS-IS PhD student @ University of Tübingen with Ulrike von Luxburg and Bedartha Goswami. Mostly thinking about deep learning theory. Also interested in ML for climate science. mohawastaken.github.io
@milago.bsky.social
PhD student in Machine Learning @ MPI-IS Tübingen, Tübingen AI Center, IMPRS-IS
@bmucsanyi.bsky.social
ELLIS & IMPRS-IS PhD Student at the University of Tübingen. Excited about uncertainty quantification, weight spaces, and deep learning theory.
@philipp.hertie.ai
Professor of Data Science @ University of Tübingen, Director of Hertie AI (www.hertie.ai) and Speaker of ML4Science (www.machinelearningforscience.org)
@elinguyen.bsky.social
PhD Student in the STAI group at the University of Tübingen and IMPRS-IS | Volunteering at KI macht Schule and Viva con Agua | Currrently visiting Vector Institute elisanguyen.github.io
@philipphennig.bsky.social
Professor for AI/ML Methods in Tübingen. Posts about Probabilistic Numerics, Bayesian ML, AI for Science. Computations are data, Algorithms make assumptions.
@auschulz.bsky.social
PhD student @mackelab.bsky.social - machine learning in (neuro)science. Co-CEO of KI macht Schule gGmbH
@coallaoh.bsky.social
Professor in Scalable Trustworthy AI @ University of Tübingen | Advisor at Parameter Lab & ResearchTrend.AI https://seongjoonoh.com | https://scalabletrustworthyai.github.io/ | https://researchtrend.ai/
@jakhmack.bsky.social
#AI4Science #CompNeuro #NeuroAI #SBI www.mackelab.org @mackelab.bsky.social · Prof Uni Tuebingen ML4Science BCCN tue.ai · Adjunct MPI IS · Fellow ellis.eu · currently hiring postdocs and PhD students · sometimes goes for a run
@roydanroy.bsky.social
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst. Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.