AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders

24 November 2020

Papers citing "AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders"

9 / 9 papers shown

Title
Alternatives of Unsupervised Representations of Variables on the Latent Space Alex Glushkovsky SSL BDL DRL 20 0 0 26 Oct 2024
Twin Auto-Encoder Model for Learning Separable Representation in Cyberattack Detection Phai Vu Dinh Nguyen Quang Uy D. Hoang Diep N. Nguyen Son Pham Bao E. Dutkiewicz AAML 76 2 0 22 Mar 2024
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies Alon Berliner Guy Rotman Yossi Adi Roi Reichart Tamir Hazan BDL DRL 35 4 0 03 May 2022
Designing Complex Experiments by Applying Unsupervised Machine Learning A. Glushkovsky 32 0 0 29 Sep 2021
Recreation of the Periodic Table with an Unsupervised Machine Learning Algorithm Minoru Kusaba Chang Liu Y. Koyama K. Terakura Ryo Yoshida 11 9 0 23 Dec 2019
Deep learning for molecular design - a review of the state of the art Daniel C. Elton Zois Boukouvalas M. Fuge Peter W. Chung AI4CE 3DV 48 328 0 11 Mar 2019
Learning Disentangled Joint Continuous and Discrete Representations Emilien Dupont DRL 47 242 0 31 Mar 2018
Adversarial Autoencoders Alireza Makhzani Jonathon Shlens Navdeep Jaitly Ian Goodfellow Brendan J. Frey GAN 53 2,224 0 18 Nov 2015
Deep Learning of Representations: Looking Forward Yoshua Bengio 78 679 0 02 May 2013