A Likelihood-Free Inference Framework for Population Genetic Data using
Exchangeable Neural Networks

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

16 February 2018

Valerio Perrone

Paul A. Jenkins

Papers citing "A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks"

17 / 17 papers shown

Title
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 625 15 0 04 Oct 2023
On the Local Minima of the Empirical Risk Chi Jin Lydia T. Liu Rong Ge Michael I. Jordan FedML 124 56 0 25 Mar 2018
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver Thomas Hubert Julian Schrittwieser Ioannis Antonoglou Matthew Lai ... D. Kumaran T. Graepel Timothy Lillicrap Karen Simonyan Demis Hassabis 139 1,769 0 05 Dec 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 294 5,827 0 14 Jun 2017
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 400 2,462 0 10 Mar 2017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs Alon Brutzkus Amir Globerson MLT 165 313 0 26 Feb 2017
Permutation-equivariant neural networks applied to dynamics prediction N. Guttenberg N. Virgo Olaf Witkowski H. Aoki Ryota Kanai 75 56 0 14 Dec 2016
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 822 5,806 0 05 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 336 4,625 0 10 Nov 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 156 158 0 20 May 2016
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network Bai Jiang Tung-Yu Wu Charles Yang Zheng W. Wong BDL 290 142 0 08 Oct 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 220 1,510 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 815 9,302 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 185 1,886 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 127 944 0 18 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.7K 150,006 0 22 Dec 2014
Non-linear regression models for Approximate Bayesian Computation M. Blum O. François 213 484 0 24 Sep 2008