deel-ai / orthogoniumLinks
New implementations of old orthogonal layers unlock large scale training.
β17Updated 3 weeks ago
Alternatives and similar repositories for orthogonium
Users that are interested in orthogonium are comparing it to the libraries listed below
Sorting:
- π Influenciae is a Tensorflow Toolbox for Influence Functionsβ63Updated last year
- Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.β58Updated 2 weeks ago
- Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layersβ96Updated 4 months ago
- Certified robustness of deep neural networksβ19Updated 10 months ago
- Documentationβ30Updated this week
- β12Updated 2 months ago
- Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers. For TensorFlow/Keras implementation, see htβ¦β32Updated 3 weeks ago
- π Overcomplete is a Vision-based SAE Toolboxβ68Updated 3 months ago
- β37Updated 2 weeks ago
- An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximizationβ130Updated last year
- LENS Projectβ48Updated last year
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.β227Updated this week
- β13Updated 2 months ago
- Python package to accelerate research on generalized out-of-distribution (OOD) detection.β12Updated last year
- π Code for : "CRAFT: Concept Recursive Activation FacTorization for Explainability" (CVPR 2023)β65Updated last year
- π Xplique is a Neural Networks Explainability Toolboxβ692Updated 9 months ago
- Repository for PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits, accepted at CVPR 2024 XAI4CV Worksβ¦β16Updated last year
- π‘ Adversarial attacks on explanations and how to defend themβ319Updated 7 months ago
- [NeurIPS 2024] CoSy is an automatic evaluation framework for textual explanations of neurons.β16Updated 3 weeks ago
- Approximating neural network loss landscapes in low-dimensional parameter subspaces for PyTorchβ336Updated last year
- MetaQuantus is an XAI performance tool to identify reliable evaluation metricsβ37Updated last year
- β12Updated 3 years ago
- RobustBench: a standardized adversarial robustness benchmark [NeurIPS 2021 Benchmarks and Datasets Track]β726Updated 3 months ago
- Certified robustness "for free" using off-the-shelf diffusion models and classifiersβ42Updated 2 years ago
- A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...β332Updated last week
- A toolkit for quantitative evaluation of data attribution methods.β49Updated last week
- Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning)β¦β251Updated this week
- [NeurIPS 2023] and [ICLR 2024] for robustness certification.β10Updated 7 months ago
- Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.β46Updated 8 months ago
- tiny-imagenet dataset downloader & reader using tensorflow_datasets (tfds) apiβ20Updated 5 years ago