henrygouk / stochastic-gradient-trees
☆10Updated 2 years ago
Alternatives and similar repositories for stochastic-gradient-trees:
Users that are interested in stochastic-gradient-trees are comparing it to the libraries listed below
- A Wasserstein Subsequence Kernel for Time Series.☆21Updated 9 months ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Ancestral Gumbel-Top-k Sampling☆23Updated 4 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated 11 months ago
- Official repository for the AAAI-21 paper 'Explainable Models with Consistent Interpretations'☆18Updated 2 years ago
- An implementation of the Hogwild! algorithm for asynchronous SGD that interfaces with sci-kit learn.☆20Updated 5 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated 11 months ago
- Code of the paper Fair k-Means Clustering☆13Updated 3 years ago
- Code for the paper "Let’s Make Block Coordinate Descent Go Fast"☆47Updated last year
- EigenPro2 iteration in Tensorflow (Keras)☆23Updated 6 years ago
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 4 years ago
- A simple algorithm to identify and correct for label shift.☆21Updated 7 years ago
- ☆30Updated 3 years ago
- Code for AAAI 2019 Network Interpretability workshop paper☆16Updated 3 years ago
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆17Updated last year
- CoLa - Decentralized Linear Learning: https://arxiv.org/abs/1808.04883☆20Updated 3 years ago
- Research prototype of deletion efficient k-means algorithms☆23Updated 5 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆30Updated 2 years ago
- [Python] Comparison of empirical probability distributions. Integral probability metrics (e.g. Kantorovich metric). f-divergences (e.g. K…☆11Updated last year
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆27Updated 4 years ago
- This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".☆14Updated 5 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆18Updated 5 years ago
- Dissecting the weight space of neural networks☆18Updated 3 years ago
- Code for paper by Bamler & Mandt, "Extreme Classification via Adversarial Softmax Approximation" (ICLR 2020)☆14Updated 4 years ago
- Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks☆12Updated 4 years ago
- code for hierarchical importance weighted autoencoders☆11Updated 5 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 3 years ago
- ☆21Updated 4 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- can calculate the Hessian matrix and/or its spectrum for simple neural nets☆10Updated 6 years ago