Nixtla/neuralforecast v1.5.0

on GitHub

What's Changed

Features

New models

• [FEAT] VanillaTransformer, Autoformer in #469
• [FEAT] StemGNN in #456
• [FEAT] PatchTST in #485
• [FEAT] Informer, augment_calendar_df, set seeds in fit and predict in #463
• [FEAT] Hierarchical Forecasting Networks (HINT) in #489

Misc

• [FEAT] Added MSSE class to losses.pytorch notebook in #468
• [FEAT] Robustified Distribution Outputs in #492
• [FEAT] Added MS availability to augment_calendar_df function in #506
• [FEAT] Add alias argument in #502
• [FEAT] mean default distribution output in addition to quantiles in #529
• [FEAT] Predict insample in #528

Fixes

• [FIX] Remove fixed lib versions in #446
• [FIX] Fixed sCRPS in losses.pytorch notebook in #462
• [FIX] Compute validation loss per epoch in #507
• [FIX] MLP/Recurrent-based memory inference complications in #512
• [FIX] Fix error with inference_input_size in #536
• [FIX] Add instructions python version in #539
• [FIX] Predict dates bug in #540
• [FIX] Autoformer in #523
• [FIX] Removed duplicate from model collection list in #517

Tutorials and Docs

• [FEAT] Electricity Peak Detection in #450
• [FEAT] Add End to End Walkthrough tutorial in #472
• [DOCS] Improved HINT documentation, and broken links in #490
• [DOCS] HINT documentation in #491
• [DOCS] HINT: Updated Unit Test and Example Notebooks in #516
• [FEAT] HINT Unit Test in #499

New dependencies

• [FEAT] Add support for lightning>=2.0.0, and torch>=2.0.0 in #498
• [FEAT] Allow pandas 2 in #508

New Contributors

• @VinishUchiha made their first contribution in #517

Full Changelog: v1.4.0...v1.5.0