automl / quicktunetool
A framework for QuickTune
☆12Updated last week
Alternatives and similar repositories for quicktunetool:
Users that are interested in quicktunetool are comparing it to the libraries listed below
- ☆15Updated 3 months ago
- [ICLR 2021] Few Shot Bayesian Optimization☆18Updated 2 years ago
- [ICLR 2023] Deep Ranking Ensembles for Hyperparameter Optimization☆13Updated 9 months ago
- [ICLR2024] Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How☆30Updated 2 months ago
- Surrogate benchmarks for HPO problems☆27Updated last week
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆24Updated 10 months ago
- In-context Bayesian Optimization☆15Updated this week
- Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.☆64Updated this week
- HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models☆18Updated last month
- A learning curve benchmark on OpenML data☆30Updated last month
- Launching and monitoring Slurm experiments in Python☆15Updated last week
- [NeurIPS DBT 2021] HPO-B☆28Updated 5 months ago
- ☆73Updated 5 months ago
- Our maintained PFN repository. Come here to train SOTA PFNs.☆56Updated 2 months ago
- TabDPT: Scaling Tabular Foundation Models☆22Updated this week
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆81Updated last year
- Official code for our NeurIPS 2024 paper "einspace: Searching for Neural Architectures from Fundamental Operations"☆25Updated 2 months ago
- [KDD 2023] Deep Pipeline Embeddings for AutoML☆15Updated 2 months ago
- Code accompanying https://arxiv.org/abs/1802.02219☆17Updated 2 years ago
- Tabular In-Context Learning☆40Updated last month
- A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks.☆11Updated this week
- ☆13Updated 3 years ago
- The first collection of surrogate benchmarks for Joint Architecture and Hyperparameter Search.☆14Updated last year
- a minimal website to get the diff of llm rewrites☆10Updated last month
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- ☆12Updated 2 years ago
- Bayesian active learning with EPIG data acquisition☆26Updated 2 weeks ago
- Collection of hyperparameter optimization benchmark problems☆144Updated 7 months ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- ☆23Updated last year