TorchDrift
loss-landscape
TorchDrift | loss-landscape | |
---|---|---|
1 | 2 | |
302 | 2,642 | |
0.0% | - | |
0.0 | 0.0 | |
over 1 year ago | about 2 years ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TorchDrift
loss-landscape
- [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process?
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[D] Visualizing loss surface in input space
Code for https://arxiv.org/abs/1712.09913 found: https://github.com/tomgoldstein/loss-landscape
What are some alternatives?
Transformer-MM-Explainability - [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
cockpit - Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both
uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
WeightWatcher - The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
explainerdashboard - Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.