stat-ml / alpacaLinks
Library for active learning and uncertainty estimation in machine learning
☆28Updated 3 years ago
Alternatives and similar repositories for alpaca
Users that are interested in alpaca are comparing it to the libraries listed below
Sorting:
- ☆82Updated 2 years ago
- Deep Learning Utilities for PyTorch users (old name: Zero)☆38Updated 9 months ago
- repository with the tutorials for MLSS Skoltech☆66Updated 6 years ago
- Code for MSID, a Multi-Scale Intrinsic Distance for comparing generative models, studying neural networks, and more!☆52Updated 6 years ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆39Updated 5 years ago
- Python implementation of GLN in different frameworks☆96Updated 5 years ago
- this repository is created to accumulate all LaTeX templates needed at Skoltech☆20Updated 7 years ago
- ☆100Updated 4 years ago
- http://nlp.seas.harvard.edu/2018/04/03/attention.html☆62Updated 4 years ago
- Deep Neural Decision Trees☆165Updated 3 years ago
- Python and torch-based package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated last month
- Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions☆259Updated 2 years ago
- repository with the lectures for MLSS Skoltech☆139Updated 6 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆85Updated 4 years ago
- Course "Theories of Deep Learning"☆195Updated 6 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Active learning☆79Updated 3 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- This repository contains data readers and examples for the three tracks of the Shifts Dataset and the Shifts Challenge.☆238Updated 2 years ago
- Python toolbox for sampling Determinantal Point Processes☆236Updated last year
- Some examples of using PyTorch for tabular data☆67Updated 5 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Theoretical Deep Learning: generalization ability☆47Updated 6 years ago
- A supplementary code for Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs.☆47Updated 6 years ago
- Learning to Initialize Neural Networks for Stable and Efficient Training☆138Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- ☆23Updated 5 years ago
- Repository with all material for SMILES, the Summer School of Machine Learning at Skoltech, taking place from the 16th to the 21st of Aug…☆55Updated 5 years ago
- A neural network architecture for prediction on sets☆24Updated 3 years ago
- BOAH: Bayesian Optimization & Analysis of Hyperparameters☆67Updated 5 years ago