Explore >> Select a destination
|
You are here 
|
tiao.io | ||
| | | | |
www.chrisstucchio.com
|
|
| | | | | In a previous job, I built a machine learning system to detect financial fraud. Fraud was a big problem at the time - for simplicity of having nice round numbers, suppose 10% of attempted transactions were fraudulent. My machine learning system worked great - as a further set of made-up round numbers ... | |
| | | | |
jxmo.io
|
|
| | | | | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents. | |
| | | | |
www.yulingyao.com
|
|
| | | | | Score matching Suppose that we observe a sequence of data $y={y_i \in R_m \mid 1\leq i \leq n}$ coming independently from an unknown distribution $p_{true}$; we would like to evaluate a forecast given by a probabilistic density function $p(y)$. For example, we may use the logarithm score $\sum_{i=1}^n \log p(y_i)$ to assess the forecast. | |
| | | | |
dennybritz.com
|
|
| | | Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming. | ||
