The review debate has entered 🦋. Let me re-propose my favorite idea so far: We reduce everything to a single point of entry with rolling review that only checks for scientific correctness (like TMLR). Once a paper is published there, you can apply for it to be presented at an upcoming conference.
24.11.2024 09:58 — 👍 45 🔁 2 💬 6 📌 1
A statistical approach to model evaluations
A research paper from Anthropic on how to apply statistics to improve language model evaluations
Great to see Anthropic highlighting the importance of uncertainty quantification (UQ) in AI.
Having spent my PhD and postdoc developing scalable UQ methods for real-world, high-dimensional problems, I’m currently on the academic job market—feel free to reach out!
21.11.2024 20:04 — 👍 9 🔁 1 💬 1 📌 1
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.
web: http://maxim.ece.illinois.edu
substack: https://realizable.substack.com
Associate Professor at Princeton
Machine Learning Researcher
FAIR Chemistry. Simulation-based Inference.
Academy Research Fellow at the Dept. of Computer Science, Aalto University, Finland. Affiliated with the Finnish Center for Artificial Intelligence.
Website: http://bharti-ayush.github.io
Lecturer (Assistant Prof) in Statistical Science at UCL.
Previously Postdoc @ Lancaster Uni, PhD @ Imperial College London, MA @ Cambridge Uni.
Interested in computational stats, probabilistic ML, optimisation.
Website: https://louissharrock.github.io/
Computational Neuroscience and Machine Learning. Group Leader at VIB-NERF (https://nerf.be/en#/) and Associate Professor at KU Leuven (https://www.kuleuven.be/english/kuleuven).
More details at goncalveslab.sites.vib.be
Senior Lecturer in Statistical Data Science at QUT in Mathematics. I do inference in ecology and biology. Stochastic modelling and Bayesian computation. Opinions=mine
Assistant professor in applied statistics at Tampere University
Likelihood-free inference|Statistical modelling|Often Bayesian|Open source software development
PhD student working on simulation-based inference under the supervision of @glouppe .
Assistant professor at NCU. Developing methods for atomistic simulations. Building a research group!
x.com/JakubRydzewski
Assistant Professor at UNC Chapel Hill, previously a postdoc at Meta AI, PhD from UPenn, a basketball enthusiast 🏀.
🔗 https://www.gedasbertasius.com/
🎓 https://scholar.google.com/citations?hl=en&user=8FWkjw8AAAAJ
International Conference on Learning Representations https://iclr.cc/
assistant prof at USC Data Sciences and Operations and Computer Science; phd Cornell ORIE.
data-driven decision-making, operations research/management, causal inference, algorithmic fairness/equity
bureaucratic justice warrior
angelamzhou.github.io
Postdoc @UNC working on NLP, AI, and computational linguistics. Formerly PhD student @JHU and undergrad @McGill
esteng.github.io
Wisconsin CS. Snorkel AI.
Working on machine learning & information theory.
https://pages.cs.wisc.edu/~fredsala/
