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End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes

25 May 2023

Papers citing "End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes"

25 / 25 papers shown

Title
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL Yu-Heng Hung Kai-Jie Lin Yu-Heng Lin Chien-Yi Wang Cheng Sun Ping-Chun Hsieh 64 1 0 28 May 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 96 3 0 03 Jan 2025
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization Zeyuan Ma Hongshu Guo Yue-Jiao Gong Jun Zhang Kay Chen Tan 293 4 0 01 Nov 2024
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling Tung Nguyen Aditya Grover BDL UQCV 85 107 0 09 Jul 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers Yutian Chen Xingyou Song Chansoo Lee Zehao Wang Qiuyi Zhang ... Greg Kochanski Arnaud Doucet MarcÁurelio Ranzato Sagi Perel Nando de Freitas 101 65 0 26 May 2022
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Jiajun He Austin Tripp José Miguel Hernández-Lobato 66 23 0 05 May 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
End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian Optimization Tomoharu Iwata BDL 47 4 0 01 Nov 2021
Pre-trained Gaussian processes for Bayesian optimization Zehao Wang George E. Dahl Kevin Swersky Chansoo Lee Zachary Nado Justin Gilmer Jasper Snoek Zoubin Ghahramani 141 46 0 16 Sep 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Katharina Eggensperger Philip Muller Neeratyoy Mallik Matthias Feurer René Sass Aaron Klein Noor H. Awad Marius Lindauer Frank Hutter 217 104 0 14 Sep 2021
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 398 1,988 0 11 Apr 2020
Data-efficient Domain Randomization with Bayesian Optimization Fabio Muratore C. Eilers Michael Gienger Jan Peters OOD 122 81 0 05 Mar 2020
Convolutional Conditional Neural Processes Jonathan Gordon W. Bruinsma Andrew Y. K. Foong James Requeima Yann Dubois Richard Turner BDL 88 168 0 29 Oct 2019
Stabilizing Transformers for Reinforcement Learning Emilio Parisotto H. F. Song Jack W. Rae Razvan Pascanu Çağlar Gülçehre ... Aidan Clark Seb Noury M. Botvinick N. Heess R. Hadsell OffRL 96 367 0 13 Oct 2019
Meta-Learning for Black-box Optimization T. Vishnu Pankaj Malhotra Jyoti Narwariya Lovekesh Vig Gautam M. Shroff 54 19 0 16 Jul 2019
Attentive Neural Processes Hyunjik Kim A. Mnih Jonathan Richard Schwarz M. Garnelo S. M. Ali Eslami Dan Rosenbaum Oriol Vinyals Yee Whye Teh 106 442 0 17 Jan 2019
Conditional Neural Processes M. Garnelo Dan Rosenbaum Chris J. Maddison Tiago Ramalho D. Saxton Murray Shanahan Yee Whye Teh Danilo Jimenez Rezende S. M. Ali Eslami UQCV BDL 88 706 0 04 Jul 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition Pavel Izmailov Alexander Novikov D. Kropotov 79 62 0 19 Oct 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 571 19,296 0 20 Jul 2017
Deep reinforcement learning from human preferences Paul Christiano Jan Leike Tom B. Brown Miljan Martic Shane Legg Dario Amodei 218 3,377 0 12 Jun 2017
One-Shot Imitation Learning Yan Duan Marcin Andrychowicz Bradly C. Stadie Jonathan Ho Jonas Schneider Ilya Sutskever Pieter Abbeel Wojciech Zaremba OffRL 86 689 0 21 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 833 11,952 0 09 Mar 2017
Reinforcement Learning with Unsupervised Auxiliary Tasks Max Jaderberg Volodymyr Mnih Wojciech M. Czarnecki Tom Schaul Joel Z Leibo David Silver Koray Kavukcuoglu SSL 111 1,229 0 16 Nov 2016
Generative Adversarial Imitation Learning Jonathan Ho Stefano Ermon GAN 165 3,125 0 10 Jun 2016
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 382 7,965 0 13 Jun 2012