automl / nepsLinks
Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
☆77Updated this week
Alternatives and similar repositories for neps
Users that are interested in neps are comparing it to the libraries listed below
Sorting:
- An interactive framework to visualize and analyze your AutoML process in real-time.☆90Updated last week
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆35Updated 2 months ago
- In-context Bayesian Optimization☆16Updated last week
- Our maintained PFN repository. Come here to train SOTA PFNs.☆120Updated last month
- Launching and monitoring Slurm experiments in Python☆20Updated 3 months ago
- ☆89Updated 6 months ago
- Tabular In-Context Learning☆93Updated 8 months ago
- A learning curve benchmark on OpenML data☆31Updated 11 months ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆239Updated last year
- Collection of hyperparameter optimization benchmark problems☆156Updated 5 months ago
- scikit-activeml: A Comprehensive and User-friendly Active Learning Library☆178Updated this week
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Repository for TabICL: A Tabular Foundation Model for In-Context Learning on Large Data☆227Updated 2 months ago
- A build-it-yourself AutoML Framework☆72Updated last year
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- [NeurIPS 2022] Supervising the Multi-Fidelity Race of Hyperparameter Configurations☆13Updated 2 years ago
- Surrogate benchmarks for HPO problems☆29Updated 5 months ago
- Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"☆61Updated last month
- Code for "TabZilla: When Do Neural Nets Outperform Boosted Trees on Tabular Data?"☆172Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- ☆155Updated 3 years ago
- The PyExperimenter is a tool for the automatic execution of experiments, e.g. for machine learning (ML), capturing corresponding results …☆38Updated last month
- Domain adaptation toolbox compatible with scikit-learn and pytorch☆144Updated 3 weeks ago
- Simple (and cheap!) neural network uncertainty estimation☆77Updated last month
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆174Updated last year
- A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks.☆17Updated last week
- 👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)☆31Updated 3 years ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆72Updated 2 years ago