vivit VS Transformer-MM-Explainability

Compare vivit vs Transformer-MM-Explainability and see what are their differences.

vivit

[TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivatives & Newton steps (by f-dangel)
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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. (by hila-chefer)
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vivit Transformer-MM-Explainability
1 3
17 715
- -
0.0 0.0
10 months ago 9 months ago
Python Jupyter Notebook
MIT License MIT License
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vivit

Posts with mentions or reviews of vivit. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

Transformer-MM-Explainability

Posts with mentions or reviews of Transformer-MM-Explainability. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

When comparing vivit and Transformer-MM-Explainability you can also consider the following projects:

pytea - PyTea: PyTorch Tensor shape error analyzer

pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

TorchDrift - Drift Detection for your PyTorch Models

backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

explainerdashboard - Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

WeightWatcher - The WeightWatcher tool for predicting the accuracy of Deep Neural Networks

shap - A game theoretic approach to explain the output of any machine learning model.

clip-italian - CLIP (Contrastive Language–Image Pre-training) for Italian

uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

vivit vs pytea Transformer-MM-Explainability vs pytorch-grad-cam vivit vs cleverhans Transformer-MM-Explainability vs TorchDrift vivit vs backpack Transformer-MM-Explainability vs explainerdashboard vivit vs WeightWatcher Transformer-MM-Explainability vs shap vivit vs TorchDrift Transformer-MM-Explainability vs clip-italian vivit vs uncertainty-toolbox Transformer-MM-Explainability vs pytea