yangarbiter / interpretable-robust-treesLinks
Connecting Interpretability and Robustness in Decision Trees through Separation
☆16Updated 4 years ago
Alternatives and similar repositories for interpretable-robust-trees
Users that are interested in interpretable-robust-trees are comparing it to the libraries listed below
Sorting:
- Explanation Optimization☆13Updated 4 years ago
- ☆38Updated 4 years ago
- Code for AAAI 2020 paper "Ensembles of Locally Independent Prediction Models"☆8Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 4 years ago
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆61Updated 2 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆24Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated 2 years ago
- ☆20Updated 5 years ago
- ☆10Updated 3 years ago
- Learning perturbation sets for robust machine learning☆65Updated 3 years ago
- "Predict, then Interpolate: A Simple Algorithm to Learn Stable Classifiers" ICML 2021☆18Updated 4 years ago
- Post-processing for fair classification☆17Updated last month
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 6 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated 2 years ago
- Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)☆28Updated 4 years ago
- ☆37Updated last year
- A fast and efficient way to compute a differentiable bound on the singular values of convolution layers☆13Updated 5 years ago
- Code for testing DCT plus Sparse (DCTpS) networks☆14Updated 4 years ago
- [ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples☆67Updated 3 weeks ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- An empirical investigation of deep learning theory☆16Updated 5 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Geometric Certifications of Neural Nets☆42Updated 2 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆52Updated 5 years ago
- Tools for robustness evaluation in interpretability methods☆10Updated 4 years ago
- ☆14Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size☆17Updated 6 years ago