84 dependents
| Package | Description | Downloads/month |
|---|---|---|
| NeuralProphet: A simple forecasting package | 114K | |
| Model explainability that works seamlessly with 🤗 transformers. Explain your tra... | 32K | |
| Sequential Parameter Optimization in Python | 13K | |
| AutoML DNN Vision Models | 6K | |
| spaCR Spatial phenotype analysis of CRISPR–Cas9 screens (spaCR) | 5K | |
| Testing with PCA projected Concept Activation Vectors | 5K | |
| gReLU is a python library to train, interpret, and apply deep learning models to... | 4K | |
| Deep learning framework for genomics and multi-modal data | 3K | |
| GUI for spotPython | 3K | |
| todo | 2K | |
| Shape Analysis Explainability And Interpretability | 2K | |
| BertNado: A framework for training and evaluating transformer-based models for C... | 2K | |
| A deep-learning based multi-omics bulk sequencing data integration suite with a ... | 2K | |
| A GAT-based computational framework to predict long-range gene regulatory relati... | 1K | |
| A python package for benchmarking interpretability techniques on Transformers. | 1K | |
| 1K | ||
| PyTorchAutoForge library is based on raw PyTorch and designed to automate DNN de... | 1K | |
| A unifying representation of single cell expression profiles that quantifies sim... | 1K | |
| Spatial phenotype analysis of crisp screens (SpaCr) | 1K | |
| A toolbox for fundus image analysis | 927 | |
| Interpretability for Sequence Generation Models 🔍 | 883 | |
| scCAMEL: single cell Cross- Annotation and Multimodal Estimation on Lineage traj... | 852 | |
| ML for sports | 832 | |
| A package for model explainability and explainability comparision for tabular da... | 639 | |
| Add a short description here! | 601 | |
| SIGnature is a Python package that empowers researchers to rapidly query gene se... | 452 | |
| A robust SHAP explainer wrapper for PyTorch Geometric models. | 416 | |
| GitHub repository that contains code for the Patch It Python project | 409 | |
| PhysioEx, a PyTorch Lightning based library for Interpretable physiological sign... | 396 | |
| Benchmarking framework for protein representation learning. Includes a large num... | 376 | |
| Explain your 🤗 transformers without effort! Plot the internal behavior of your m... | 375 | |
| Benchmark to Evaluate EXplainable AI | 340 | |
| Unified Model Interpretability Library for Time Series | 332 | |
| Samples generation utilities managed with uv | 324 | |
| Graph Neural Network Library Built On Top Of PyTorch and PyTorch Geometric | 318 | |
| Frequency-domain model explanation (IG) package | 314 | |
| Amulet is a Python machine learning (ML) package to evaluate the susceptibility ... | 302 | |
| Package for Explanations of Remote Sensing Imagery | 297 | |
| Explainable AI, Model Monitoring, and Outlier Detection Tools for Computer Visio... | 295 | |
| House Price Indices in Python. | 295 | |
| A library for bias detection and explainable AI methods in NLP models. | 290 | |
| Sample- And Population-Level Causal Discovery from Event Sequences using Autoreg... | 279 | |
| A comprehensive toolkit for fine-tuning and inference with DNA Language Models | 261 | |
| Integrated image classification and semantic segmentation package | 240 | |
| A framework to explain the latent representations of unsupervised black-box mode... | 229 | |
| XAI Recommendation Toolkit | 229 | |
| joltml unravels the dark side of machine learning models | 219 | |
| Interpreting sequence-to-function machine learning models | 204 | |
| TorchXAI is a PyTorch-based toolkit designed for evaluating machine learning mod... | 198 | |
| Repository for TSP 2022 | 194 |
