Top news of the week: 08.07.2021.
Research
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data
In many machine learning applications, one uses pre-trained neural networks, having limited access to training and test data. Martin et al. show how to predict trends in the quality of such ...
Unveiling Cambridge-1: The UK’s Most Powerful AI Supercomputer
Tap into massively powerful computing resources to fully harness the capabilities of AI.
Graphcore Celebrates a Stunning Loss at MLPerf Training v1.0
We dig into the strange case where Graphcore celebrated a stunning performance and price/ performance loss to NVIDIA in MLPerf Training v1.0
Meta Learning: How To Learn Deep Learning And Thrive In The Digital World
I learned to program and do deep learning using online resources. Most of my income over the last two years has come from deep learning roles. How did I do it? What did I learn along the ...
![[N] A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification](https://preview.redd.it/n4j8ip6dtn971.jpg?width=1756&format=pjpg&auto=webp&s=348ef451307158a6396ba2cf5941b4b9f670e292)
[N] A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
9 votes and 1 comment so far on Reddit
Comparing images in frequency domain. “Spectral loss” – does it make sense?
Recently, numerous academic papers in the machine learning / computer vision / image processing domains (re)introduce and discuss a “frequency loss function” or “spectral loss” – …
Savage Award
“Jimmie” Savage, is bestowed each year to two outstanding doctoral dissertations in Bayesian econometrics and statistics, one each in: Theory and Methods: for a dissertation that …