Posts in en
Mistral 7B: Decoding the Complexities of a Large Autoregressive Language Model
The goal of this post is to offer a clear understanding of how large language models like Mistral work ([Jiang et al., 2023]).
Detecting Trend Changes in Time-Series Data: A Frequentist and Parametric Approach
- 11 October 2023
- Language: en
- Category: change-point detection
Detecting trend changes in time-series can offer valuable insights for various applications. There are multiple ways to approach this problem, and each method comes with its own set of assumptions and intricacies.
Why Linear Regression is Called “Regression”: regression towards mediocrity
Linear regression is a widely used statistical technique that aims to model the relationship between a dependent variable and one or more independent variables. It plays a crucial role in various fields, including economics, social sciences, healthcare, and engineering. But have you ever wondered why this powerful modeling technique is called “regression”?
How to reduce the amount of labelled data required for your Deep Learning model with a human in the loop?
- 14 May 2023
- Language: en
- Category: deep-learning
In this blog post, we will explore how Bayesian active learning can be used to reduce the amount of labeled data required for a deep learning model with a human in the loop in the context of a classification task.
Dropout as a way to Model Uncertainty in Deep Learning Models
- 09 April 2023
- Language: en
- Category: deep-learning
In [Gal and Ghahramani, 2016], the authors propose an easy, fast and scalable method to quantify the uncertainty of any deep learning model (including big modern architectures) as long as dropout is used during training time.
Notes on Bayesian Online Change Point Detection
- 04 September 2022
- Language: en
- Category: change-point detection
In this post we are going to delve into the mathematical details behind the graphical model Bayesian Online Change Point Detection introduced in [Adams and MacKay, 2007]. This model can be used to detect different type of change-points and has known many extensions over the last few years.
