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We're hiring Summer Interns! Join our NYC team to work on cutting-edge synthetic data generation for LLMs. This is a unique opportunity to dive into foundation models, and make a real impact. If interested, feel free to share your resume with me! amazon.jobs/en/jobs/279370…
amazon.science
Amazon opens new AI lab in San Francisco focused on long-term research bets
The Amazon AGI SF Lab will focus on developing new foundational capabilities for enabling useful AI agents.
Another day another launch 😬 🚀🥳 I am super excited to announce that we open sourced Renate, a #ContinualLearning library to automatically retrain and retune #DeepNeuralNetworks. This is joined work with @610v4nn1__ , @lukas_balles and Martin Wistuba! github.com/awslabs/Renate
github.com
GitHub - awslabs/Renate: Library for automatic retraining and continual learning
Library for automatic retraining and continual learning - awslabs/Renate
A new release of Syne Tune is out! syne-tune.readthedocs.io/en/latest/inde… 🥳 Our goal is to make machine learning more reproducible. The library offers a broad range of asynchronous hyperparameter optimisation algorithms that can be run locally or in the cloud. #hpo #automl #DeepLearning
The (early) Christmas gift you all have been waiting for ;-). New release of Syne Tune! Key changes are a much better documentation, support of SageMaker warm pools and integration of YAHPO. github.com/awslabs/syne-t… Thanks to the team for this great effort!
The first version of our #hpo chapter for the D2L book is out! d2l.ai/chapter_hyperp… . This is joint work with @cedapprox and Matthias Seeger.
We are excited to announce the general availability of #Fortuna , an #OpenSource library for #UncertaintyQuantification in #DeepLearning. - #AWS blog post: lnkd.in/eKrnyK9h - #GitHub repo: github.com/awslabs/fortuna - Documentation: lnkd.in/eY9_ATj7
github.com
GitHub - awslabs/fortuna: A Library for Uncertainty Quantification.
A Library for Uncertainty Quantification. Contribute to awslabs/fortuna development by creating an account on GitHub.
Time to share our paper “Black-box Coreset Variational Inference” accepted to #NeurIPS2022 with @neuralvertigo and Hippolyt Ritter. We re-derive Bayesian core sets under an approximate inference lens to make them generally applicable. Paper link arxiv.org/abs/2211.02377 1/n
Diffusion models like #DALLE and #StableDiffusion are state of the art for image generation, yet our understanding of them is in its infancy. This thread introduces the basics of how diffusion models work, how we understand them, and why I think this understanding is broken.🧵
As many Ukrainian IT engineers right now I was left without a job 😔I am a Data Scientist with 5 years of experience in full-cycle ML models development (including deployment) and in managing data science teams. If anyone sees job positions I could fit, ping me 🙏❤️
Give, I say, all your strength to your work, make it your total concern. And don’t forget your work even in times of trial or when you near your end.
Good times! Welcome to two new members on the team, Dionysis Manousakas @neuralvertigo and Hippolyt Ritter, who will be working with me on the interface of deep learning and probabilistic inference. Very excited to work with both of you!
He who hopes to grow in spirit will have to free himself from obedience and respect.
The Call for Papers for #AISTATS2020 is out at aistats.org The submission deadline is 8 October 2019. The conference will be held in Palermo, Italy, from 3 to 5 June 2020.
Mathematicians Caucher Birkar, Alessio Figalli, Peter Scholze and Akshay Venkatesh have just been awarded the Fields Medal. Computer scientist Constantinos Daskalakis won the Nevanlinna Prize. Read our exclusive, in-depth profiles of all five winners. buff.ly/2OzGetJ
Judea Pearl claims all we do in ML is curve fitting. I wrote this post to explain that claim and introduce the basics of causal inference to ML folks. Machine Learning beyond Curve Fitting: An Intro to Causal Inference and do-Calculus inference.vc/p/f01e8d56-511…
inference.vc
ML beyond Curve Fitting: An Intro to Causal Inference and do-Calculus
Since writing this post back in 2018, I have extended this to a 4-part series on causal inference: * ➡️️ Part 1: Intro to causal inference and do-calculus [https://www.inference.vc/untitled] * Part...
RIP #MaryamMirzakhani. To learn about her math and life, this piece by @EricaKlarreich is a fine place to start. quantamagazine.org/maryam-mirzakh…
quantamagazine.org
A Tenacious Explorer of Abstract Surfaces | Quanta Magazine
Maryam Mirzakhani, who became the first woman Fields medalist for drawing deep connections between topology, geometry and dynamical systems, has died of cancer at the age of 40. This is our 2014…
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