C1510 / agd_expLinks
Experimental version of jxbz/agd implementing support for bias terms, affine parameters, transformers, etc.
☆12Updated 2 years ago
Alternatives and similar repositories for agd_exp
Users that are interested in agd_exp are comparing it to the libraries listed below
Sorting:
- A Library for Scaling Mixed-Integer Optimization-Based Machine Learning.☆12Updated last year
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆20Updated 3 years ago
- Neural Tangent Kernel (NTK) module for the scikit-learn library☆25Updated last year
- Investigate the speed of adaptation of structural causal models☆15Updated 4 years ago
- Hyperparameter tuning via uncertainty modeling☆49Updated last year
- Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…☆24Updated last year
- notebooks of cool EBM visualizations☆15Updated 4 years ago
- Quantification of Uncertainty with Adversarial Models☆29Updated 2 years ago
- ☆10Updated 2 years ago
- Some small scale experiments for my blog posts 📝☆80Updated 3 years ago
- Companion code for a tutorial on using Hydra.☆30Updated 4 years ago
- Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.☆31Updated 3 years ago
- A Python package for generating concise, high-quality summaries of a probability distribution☆56Updated 2 months ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Updated 5 years ago
- ☆18Updated 9 months ago
- AutoML Two-Sample Test☆19Updated 3 years ago
- This repository hosts the code to port NumPy model weights of BiT-ResNets to TensorFlow SavedModel format.☆14Updated 4 years ago
- Data Twinning☆25Updated 3 years ago
- Cross-prediction-powered inference☆15Updated last year
- Fast Differentiable Forest lib with the advantages of both decision trees and neural networks☆78Updated 4 years ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 3 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- ☆60Updated 3 years ago
- Neat Bayesian machine learning examples☆58Updated last month
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- A Gentle Principled Introduction to Deep Reinforcement Learning☆19Updated 9 months ago
- 💡 Learnergy is a Python library for energy-based machine learning models.☆69Updated last week
- Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX☆92Updated last year
- Causal Impact but with MFLES and conformal prediction intervals☆33Updated last year
- List of awesome JAX resources☆13Updated 3 years ago