v0.13.0

[ValerianRey]

🥝 MoDo, STCH, GeometricMean

This release introduces:

• MoDo, a weighting method from Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. Thanks a lot to @KhusPatel4450 for the contribution!
• STCH, a scalarizer from Smooth Tchebycheff Scalarization for Multi-Objective Optimization. Thanks a lot to @ppraneth for the contribution!
• GeometricMean, a scalarizer from MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning. Thanks a lot to @ppraneth for the contribution!

Changelog

Added

• Added STCH from Smooth Tchebycheff Scalarization for Multi-Objective
  Optimization, a Scalarizer that combines the input
  tensor of values into a smooth approximation of their (weighted, shifted) maximum.
• Added MoDoWeighting from Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance (JMLR 2024). It is a stateful Weighting that maintains task weights across calls via a simplex-projected gradient step on a cross-batch matrix G = J_1 @ J_2.T, computed from two independent mini-batches using autojac.jac.
• Added GeometricMean (also known as GLS) studied in MultiNet++: Multi-Stream Feature
  Aggregation and Geometric Loss Strategy for Multi-Task
  Learning,
  a Scalarizer that returns the geometric mean of the input tensor of values.

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This discussion was created from the release v0.13.0.