Brains, Sex, and Machine Learning
On 14 Apr, 2023 By admin 0 Comments
External Course
Topological Data Analysis and Machine Learning Theory - DSA ADS Course 2023
On 14 Apr, 2023 By admin 0 Comments
DSA ADS Course 2023
This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.
Discuss topological data analysis and machine learning theory in real world scenarios.
A New Kind of Science - Computational Experiments
On 14 Apr, 2023 By admin 0 Comments
Data Augmentation Can Improve Robustness - DSA ADS Course 2023
On 14 Apr, 2023 By admin 0 Comments
DSA ADS Course 2023
This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.
Discuss reducing robust overfitting by using common data augmentation schemes. When combined with model weight averaging, data augmentation can significantly boost robust accuracy.
Compare various augmentations techniques and observe that spatial composition techniques work the best for adversarial training.
Scaling Laws for Neural Language Models
On 14 Apr, 2023 By admin 0 Comments
January, 2020
Abstract
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
On 14 Apr, 2023 By admin 0 Comments
January, 2023
Abstract
BBQ: A Hand-Built Bias Benchmark for Question Answering
On 14 Apr, 2023 By admin 0 Comments
March, 2022
Abstract
The Capacity for Moral Self-Correction in Large Language Models
On 14 Apr, 2023 By admin 0 Comments
February, 2023
Abstract
Predictability and Surprise in Large Generative Models
On 14 Apr, 2023 By admin 0 Comments
June, 2022
Abstract
Random Forests - DSA ADS Course 2023
On 14 Apr, 2023 By admin 0 Comments
DSA ADS Course 2023
This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.
Discuss application random forests in real world scenarios.