## When and How

The discussions are hosted online in Lark/Wechat.

- Lark is our primary communication channel.
- Join the group using

- Wechat is mostly for our backup plans.

If you would like to be part of the party, please create a post here on GitHub discussions.

The discussions are mostly in Chinese.

### When

This is a bi-weekly meetup.

There are two different ways to keep track of the upcoming events:

- add this ics to your calendar.
- Calendar ics url: Add this ICS to your calendar app to follow the upcoming events.

- If you would like to add individual events by yourself, use the “
**Add to Calendar**” button on the specific event page.- Here is the button:

As a preview of the events, here is a calendar web page for the upcoming events (Calendar Page):

### Rules

- Everyone shall get their chance to lead the discussion.
- The first principle is to understand the content. Interrupt and ask any questions to make sure we all understand the content well.

## Why this Topic

Conditional probability estimation is one of the most fundamental problems in statistics.

- Conditional probability estimation is frequently used in solving both real life and academic problems. One is likely to encounter this problem at some point of their life.
- If you are inferring, you are probably using conditional probabilities. It is a perspective.
- There are many models and methods to estimate the conditional probability. We can learn about and from these models and methods.
- We need a universal model to solve this problem for productivity. A universal model for this task will save us a lot of time and energy.
- Many machine learning methods are based on conditional probabilities.
- Many classifiers
- Bayesian networks
- …

## What is Our Approach

- Read and Discuss
- Apply on toy problems

### Reading List and References

We will update this list on our way forward. Here is a partial list of references.

## Initial Proposal (Outdated)

As a start this is an outline of what should be covered.

- What is the conditional probability?
- Sampling theory
- Bayes
- Representation of a conditional probability

- Statistical methods to estimate the conditional probability
- The list is enormous. We will only concentrate on the basics.

- Tree-based
- Tree as “clustering” method
- Application on the bike-sharing problem

- NN-based
- NN as feature transformations
- Application on the bike-sharing problem

- EM Methods
- Variational Methods
- Normalizing Flow
- To be added as we learn more about it

## oy Problems (Outdated)

We have prepared dataset that can be used both for classification problems and regression problems.

## Tools

- Timezone conversions: World Clock