Teodor Chiaburu's repositories
beexplainable
XAI Experiments on an Annotated Dataset of Wild Bee Images
alibi
Algorithms for explaining machine learning models
Augmentor
Image augmentation library in Python for machine learning.
calibrated_explanations
Repository for the explanation method Calibrated Explanations (CE)
ConceptBottleneck
Concept Bottleneck Models, ICML 2020
Deformable-ProtoPNet
The official repository for Deformable ProtoPNet, as described in "Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes".
Webscraper_IMDB
Project for Advanced Software Engineering, Master Data Science
cxplain
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
geometric-smote
Implementation of the Geometric SMOTE over-sampling algorithm.
Git-Commands
A list of commonly used Git commands
influenciae
👋 Influenciae is a Tensorflow Toolbox for Influence Functions
interpretability-by-parts
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
lang-segment-anything
SAM with text prompt
MMAL-Net
This is a PyTorch implementation of the paper "Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization (MMAL-Net)" (Fan Zhang, Meng Li, Guisheng Zhai, Yizhao Liu).
nlxgpt
NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks, CVPR 2022 (Oral)
ProtoPNet
This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).
ProtoPool
Code for "Interpretable image classification with differentiable prototypes assignment", ECCV 2022
ProtoTree
ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021
pytorch-forecasting
Time series forecasting with PyTorch
Quantus
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
tcav
Merged repositories for TCAV and ACE
TEASER
TEASER - Tool for Energy Analysis and Simulation for Efficient Retrofit
teodorchiaburu.github.io
Portfolio Website
tf-explain
Interpretability Methods for tf.keras models with Tensorflow 2.x
xplique
👋 Xplique is a Neural Networks Explainability Toolbox
yolov7
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥