Minimal auto-differentiation engine in Rust (for educational purposes)
10 months ago
- #automatic-differentiation
- #Rust
- #machine-learning
- Minimal automatic-differentiation engine written in Rust.
- Demo trains a tiny Multi-Layer Perceptron to learn the XOR function.
- Writes a rendered computation graph of a single Perceptron to graph.html.
- Example usage with Scalar objects for automatic differentiation.
- Scalar stores value, gradient, and operation details.
- Operator overloads and helpers build a directed acyclic graph.
- backward() propagates gradients recursively through the graph.
- Graph visualization with plot::dump_graph emits a D3.js HTML file.