GitiHubi / courseMLDLLinks
A series of interactive labs we prepared for the Introduction into Machine Learning and Deep Learning course. The content of the series is based on Python, IPython Notebook, and PyTorch.
☆11Updated 4 years ago
Alternatives and similar repositories for courseMLDL
Users that are interested in courseMLDL are comparing it to the libraries listed below
Sorting:
- A series of interactive labs we prepared for the Introduction into Artificial Intelligence and Machine Learning course. The content of th…☆17Updated 4 years ago
- Reading history for Fair ML Reading Group in Melbourne☆36Updated 3 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆72Updated 2 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Supplemental Material for the ESANN 2019 Submission "Preserving privacy using synthetic data models and applications in health informatic…☆19Updated 5 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆30Updated 3 years ago
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)☆48Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)☆10Updated 2 years ago
- ☆13Updated 4 years ago
- A collection of implementations of fair ML algorithms☆12Updated 7 years ago
- All about explainable AI, algorithmic fairness and more☆109Updated last year
- COR-GAN: Correlation-Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records☆57Updated 4 years ago
- Kaggle Heritage Health Prize Challenge☆19Updated last year
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- Fairness toolkit for pytorch, scikit learn and autogluon☆32Updated 5 months ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Continual Learning in Recurrent Neural Networks☆37Updated 3 years ago
- Contains public materials for students enrolled in MITx: 6.871x, Machine Learning for Healthcare☆20Updated 3 years ago
- Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Wo…☆88Updated 5 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆54Updated 2 years ago
- Synthetic data generation by a Variational AutoEncoder with Differential Privacy assessed using Synthetic Data Vault metrics☆45Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2021.☆93Updated 3 years ago
- ☆33Updated 11 months ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆66Updated 2 years ago
- Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs☆45Updated last year
- ☆17Updated last year