feat: add probabilistic forecaster interface (decoupled from Graph-EFM)#678

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Sir-Sloth-The-Lazy:feat/probabilistic-forecaster-module

Commits on Jun 21, 2026

feat: add latent encoder/decoder infrastructure for Graph-EFM port
Sir-Sloth-The-Lazy
committed
Update neural_lam/models/latent/constant_encoder.py

Sir-Sloth-The-Lazy
and
joeloskarsson
committed
feat: address review feedback on latent encoder/decoder infra
Sir-Sloth-The-Lazy
committed
style: apply black formatting to hierarchical latent modules
Sir-Sloth-The-Lazy
committed
feat: add GraphEFM single-step probabilistic predictor (PR-6)
Sir-Sloth-The-Lazy
committed
refactor: hard-code constrained latent GNN types, reuse existing flags for the rest
Sir-Sloth-The-Lazy
committed
fix: satisfy interrogate docstring coverage from upstream main
Sir-Sloth-The-Lazy
committed
docs: describe current code only in docstrings and comments
Sir-Sloth-The-Lazy
committed
docs: convert latent module and make_gnn_seq docstrings to numpy style
Sir-Sloth-The-Lazy
committed
refactor: skip on-mesh/intra-level processing explicitly instead of IdentityModule
Sir-Sloth-The-Lazy
committed
docs: align ConstantLatentEncoder.compute_dist_params docstring with base class
Sir-Sloth-The-Lazy
committed
Update neural_lam/models/latent/base_decoder.py

Sir-Sloth-The-Lazy
and
joeloskarsson
committed
docs: expand parameter descriptions in latent decoder docstrings
Sir-Sloth-The-Lazy
committed
docs: clarify role of grid update MLP in latent decoder forward
Sir-Sloth-The-Lazy
committed
docs: explain mean/std chunking of decoder output parameters
Sir-Sloth-The-Lazy
committed
refactor: split Graph-EFM into hierarchical and flat subclasses
Sir-Sloth-The-Lazy
committed
refactor: avoid processor terminology in Graph-EFM parameters
Sir-Sloth-The-Lazy
committed
docs: document all constructor parameters in Graph-EFM subclasses
Sir-Sloth-The-Lazy
committed
refactor: remove sample_obs_noise option from Graph-EFM
Sir-Sloth-The-Lazy
committed
refactor: extract shared graph-setup helpers to remove duplication
Sir-Sloth-The-Lazy
committed
refactor: give descriptive names to Graph-EFM grid embedding methods
Sir-Sloth-The-Lazy
committed
refactor: drop redundant last_state alias in Graph-EFM forward
Sir-Sloth-The-Lazy
committed
Update neural_lam/utils.py

Sir-Sloth-The-Lazy
and
joeloskarsson
committed
feat: add probabilistic forecaster interface decoupled from Graph-EFM
Sir-Sloth-The-Lazy
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feat: add probabilistic forecaster interface (decoupled from Graph-EFM)#678

feat: add probabilistic forecaster interface (decoupled from Graph-EFM)#678
Sir-Sloth-The-Lazy wants to merge 24 commits into
mllam:mainfrom
Sir-Sloth-The-Lazy:feat/probabilistic-forecaster-module

Commits on Jun 21, 2026

feat: add latent encoder/decoder infrastructure for Graph-EFM port

Update neural_lam/models/latent/constant_encoder.py

feat: address review feedback on latent encoder/decoder infra

style: apply black formatting to hierarchical latent modules

feat: add GraphEFM single-step probabilistic predictor (PR-6)

refactor: hard-code constrained latent GNN types, reuse existing flags for the rest

fix: satisfy interrogate docstring coverage from upstream main

docs: describe current code only in docstrings and comments

docs: convert latent module and make_gnn_seq docstrings to numpy style

refactor: skip on-mesh/intra-level processing explicitly instead of IdentityModule

docs: align ConstantLatentEncoder.compute_dist_params docstring with base class

Update neural_lam/models/latent/base_decoder.py

docs: expand parameter descriptions in latent decoder docstrings

docs: clarify role of grid update MLP in latent decoder forward

docs: explain mean/std chunking of decoder output parameters

refactor: split Graph-EFM into hierarchical and flat subclasses

refactor: avoid processor terminology in Graph-EFM parameters

docs: document all constructor parameters in Graph-EFM subclasses

refactor: remove sample_obs_noise option from Graph-EFM

refactor: extract shared graph-setup helpers to remove duplication

refactor: give descriptive names to Graph-EFM grid embedding methods

refactor: drop redundant last_state alias in Graph-EFM forward

Update neural_lam/utils.py

feat: add probabilistic forecaster interface decoupled from Graph-EFM