A Generative Model for Sampling High-Performance and Diverse Weights for
Neural Networks

A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks

7 May 2019

Erik Nijkamp

Papers citing "A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks"

8 / 8 papers shown

Title
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes V. Chauhan Lei A. Clifton Gaurav Nigam David Clifton CML 63 0 0 12 Feb 2025
Principled Weight Initialization for Hypernetworks Oscar Chang Lampros Flokas Hod Lipson 30 73 0 13 Dec 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation V. Chauhan Jiandong Zhou Ghadeer O. Ghosheh Soheila Molaei David Clifton 30 8 0 25 May 2023
Permutation Equivariant Neural Functionals Allan Zhou Kaien Yang Kaylee Burns Adriano Cardace Yiding Jiang Samuel Sokota J. Zico Kolter Chelsea Finn 35 47 0 27 Feb 2023
Learning to Learn with Generative Models of Neural Network Checkpoints William S. Peebles Ilija Radosavovic Tim Brooks Alexei A. Efros Jitendra Malik UQCV 75 65 0 26 Sep 2022
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 274 5,330 0 05 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 186 1,186 0 30 Nov 2014