hcarlens / pytorch-tabular
Some examples of using PyTorch for tabular data
☆65Updated 4 years ago
Alternatives and similar repositories for pytorch-tabular:
Users that are interested in pytorch-tabular are comparing it to the libraries listed below
- ☆201Updated 3 years ago
- A way to use N-Beats in fastai for sequence data☆59Updated last year
- ☆26Updated 5 years ago
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆82Updated 2 years ago
- Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"☆62Updated 2 years ago
- This repository contains code for the paper: https://arxiv.org/abs/1905.03806. It also contains scripts to reproduce the results in the p…☆168Updated 5 years ago
- ☆16Updated 2 years ago
- Scikit-learn compatible implementation of the Gauss Rank scaling method☆73Updated last year
- Improved TabNet for TensorFlow☆52Updated 2 years ago
- Revisiting Pretrarining Objectives for Tabular Deep Learning☆63Updated 2 years ago
- ☆97Updated 2 weeks ago
- Reusable BatchBALD implementation☆78Updated last year
- Collection of the latest, greatest, deep learning optimizers (for Pytorch) - CNN, NLP suitable☆212Updated 4 years ago
- Easy Custom Losses for Tree Boosters using Pytorch☆34Updated 4 years ago
- Python implementation of GLN in different frameworks☆98Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆130Updated 4 years ago
- Distillation of Neural Network Into a Soft Decision Tree☆65Updated 5 years ago
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆64Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 10 months ago
- Calibration of Convolutional Neural Networks☆161Updated last year
- Implementation of ETSformer, state of the art time-series Transformer, in Pytorch☆152Updated last year
- An example of using a discriminator to correct for a difference in the distributions between the training and test data.☆67Updated 8 years ago
- Easy-to-use AdaHessian optimizer (PyTorch)☆77Updated 4 years ago
- Implementations of quasi-hyperbolic optimization algorithms.☆102Updated 4 years ago
- Drift Detection for your PyTorch Models☆315Updated 2 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Repository for Multimodal AutoML Benchmark☆65Updated 3 years ago
- Learning error bars for neural network predictions☆70Updated 5 years ago
- Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)☆58Updated last year
- A scikit-learn compatible implementation of hyperband☆76Updated 5 years ago