Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks

31 October 2023

Steven Adriaensen

Herilalaina Rakotoarison

Papers citing "Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks"

20 / 20 papers shown

Title
ForecastPFN: Synthetically-Trained Zero-Shot Forecasting Samuel Dooley Gurnoor Singh Khurana Chirag Mohapatra Siddartha Naidu Colin White AI4TS 139 66 0 03 Nov 2023
PFNs4BO: In-Context Learning for Bayesian Optimization Samuel G. Müller Matthias Feurer Noah Hollmann Frank Hutter 75 41 0 27 May 2023
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 111 315 0 05 Jul 2022
Supervising the Multi-Fidelity Race of Hyperparameter Configurations Martin Wistuba Arlind Kadra Josif Grabocka 83 15 0 20 Feb 2022
Learning Curves for Decision Making in Supervised Machine Learning: A Survey F. Mohr Jan N. van Rijn 104 55 0 28 Jan 2022
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 86 170 0 20 Dec 2021
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL Lucas Zimmer Marius Lindauer Frank Hutter MU 118 92 0 24 Jun 2020
Using a thousand optimization tasks to learn hyperparameter search strategies Luke Metz Niru Maheswaranathan Ruoxi Sun C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 89 46 0 27 Feb 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 638 4,921 0 23 Jan 2020
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search Xuanyi Dong Yi Yang 144 714 0 02 Jan 2020
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings Matilde Gargiani Aaron Klein Stefan Falkner Frank Hutter BDL 62 12 0 10 Oct 2019
An Open Source AutoML Benchmark Pieter Gijsbers E. LeDell Janek Thomas Sébastien Poirier B. Bischl Joaquin Vanschoren VLM 63 241 0 01 Jul 2019
BOHB: Robust and Efficient Hyperparameter Optimization at Scale Stefan Falkner Aaron Klein Frank Hutter BDL 211 1,102 0 04 Jul 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 803 132,454 0 12 Jun 2017
Designing Neural Network Architectures using Reinforcement Learning Bowen Baker O. Gupta Nikhil Naik Ramesh Raskar 132 1,472 0 07 Nov 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 350 8,179 0 13 Aug 2016
OpenML: networked science in machine learning Joaquin Vanschoren Jan N. van Rijn B. Bischl Luís Torgo FedML AI4CE 179 1,328 0 29 Jul 2014
Freeze-Thaw Bayesian Optimization Kevin Swersky Jasper Snoek Ryan P. Adams 103 270 0 16 Jun 2014
Deep Gaussian Processes Andreas C. Damianou Neil D. Lawrence GP BDL 149 1,184 0 02 Nov 2012
emcee: The MCMC Hammer D. Foreman-Mackey D. Hogg D. Lang J. Goodman 92 8,538 0 16 Feb 2012