Comments (2)
Would the following be enough?
build: The network constructor (e.g. :class:`lampe.nn.ResMLP`). It takes the
number of input and output features as positional arguments.
For the embedding tutorial, the following paragraph explains why we need an embedding. Should we add something?
Because the observations are images, they cannot be fed directly to a
NPE
module, which only accepts vector-shaped observations. Instead, we rely on a convolutional neural network to extract a vector of informative features from the observation and feed this vector to the density estimator. In our case, the latter is a neural spline flow (NSF) with rational-quadratic splines borrowed from thezuko
package.
from lampe.
The constructor descriptions have been updated in 83fd155.
from lampe.
Related Issues (9)
- Add unit tests HOT 1
- Implement Balanced Neural Ratio Estimation loss HOT 1
- Incorrect grid shape in `utils.gridapply` for one-dimensional space
- Implement a score-based inference algorithm
- Tutorial does not agree with API HOT 2
- Implement differentiable coverage probability regularizer HOT 1
- Deal with time-dependent or time-series data HOT 12
- Differences in batched vs. non-batched FMPE log_prob HOT 5
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from lampe.