Wildfire Mamba¶

Overview¶

wildfire_mamba models county-day ERA5 sequences by combining selective state-space temporal blocks with a simple spatial graph layer.

At a Glance¶

Hazard Family

Wildfire

Public catalog grouping used for this model.

Maturity

Hidden

Catalog maturity label used on the index page.

Tasks

Classification

Benchmark Family

Unmapped

Primary benchmark-family link used for compatible evaluation coverage.

Description¶

wildfire_mamba models county-day ERA5 sequences by combining selective state-space temporal blocks with a simple spatial graph layer.

The PyHazards implementation targets binary next-day per-county wildfire classification and supports an optional count head for multi-task extensions.

Benchmark Compatibility¶

Primary benchmark family: Not yet mapped.

External References¶

Paper: Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Registry Name¶

Primary entrypoint: wildfire_mamba

Supported Tasks¶

Classification

Programmatic Use¶

import torch
from pyhazards.models import build_model

model = build_model(
    name="wildfire_mamba",
    task="classification",
    in_dim=3,
    num_counties=4,
    past_days=5,
)

x = torch.randn(2, 5, 4, 3)
logits = model(x)
print(logits.shape)

Notes¶

The CI smoke test validates the default binary-classification path on synthetic data.