SimplexLab/TorchJD
Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).
306 stars and 985 monthly downloads. Available on PyPI.
Stars
306
Forks
15
Language
Python
License
MIT
Category
Last pushed
Mar 11, 2026
Monthly downloads
985
Commits (30d)
0
Dependencies
4
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/SimplexLab/TorchJD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
metaopt/torchopt
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
opthub-org/pytorch-bsf
PyTorch implementation of Bezier simplex fitting
pytorch/xla
Enabling PyTorch on XLA Devices (e.g. Google TPU)
clovaai/AdamP
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)
nschaetti/EchoTorch
A Python toolkit for Reservoir Computing and Echo State Network experimentation based on...