Learning Latent Subspaces in Variational Autoencoders

14 December 2018

Papers citing "Learning Latent Subspaces in Variational Autoencoders"

30 / 30 papers shown

Title
GPO-VAE: Modeling Explainable Gene Perturbation Responses utilizing GRN-Aligned Parameter Optimization Seungheun Baek Soyon Park Y. T. Chok Mogan Gim Jaewoo Kang DRL 47 0 0 31 Jan 2025
Disentangling representations of retinal images with generative models Sarah Muller Lisa M. Koch Hendrik P. A. Lensch Philipp Berens MedIm 32 3 0 29 Feb 2024
A multimodal dynamical variational autoencoder for audiovisual speech representation learning Samir Sadok Simon Leglaive Laurent Girin Xavier Alameda-Pineda Renaud Séguier 33 11 0 05 May 2023
Generating Features with Increased Crop-related Diversity for Few-Shot Object Detection Jingyi Xu Hieu M. Le Dimitris Samaras ObjD 23 26 0 11 Apr 2023
Multi-objective Deep Data Generation with Correlated Property Control Shiyu Wang Xiaojie Guo Xuanyang Lin Bo Pan Yuanqi Du ... S. Alkhalifa K. Minbiole Bill Wuest Amarda Shehu Liang Zhao AI4CE 54 14 0 01 Oct 2022
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space Eric Yeh Pedro Sequeira Jesse Hostetler Melinda Gervasio OOD CML BDL OffRL 25 2 0 15 Jul 2022
Comparing the latent space of generative models Andrea Asperti Valerio Tonelli DRL 26 12 0 14 Jul 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 26 49 0 20 Jun 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models Xiaoting Shao Kristian Kersting BDL 22 1 0 16 May 2022
Learning Conditional Invariance through Cycle Consistency M. Samarin V. Nesterov Mario Wieser Aleksander Wieczorek S. Parbhoo Volker Roth 39 3 0 25 Nov 2021
Group-disentangled Representation Learning with Weakly-Supervised Regularization Linh-Tam Tran Amir Hosein Khasahmadi Aditya Sanghi Saeid Asgari Taghanaki DRL 34 1 0 23 Oct 2021
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models Maciej Wołczyk Magdalena Proszewska Lukasz Maziarka Maciej Ziȩba Patryk Wielopolski Rafał Kurczab Marek Śmieja DRL 27 5 0 18 Sep 2021
Efficient Out-of-Distribution Detection Using Latent Space of $β$ -VAE for Cyber-Physical Systems Shreyas Ramakrishna Zahra Rahiminasab G. Karsai Arvind Easwaran Abhishek Dubey OODD 19 27 0 26 Aug 2021
Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning Chandrajit L. Bajaj A. Roy Haoran Zhang BDL DRL 26 1 0 25 Jul 2021
Promises and Pitfalls of Black-Box Concept Learning Models Anita Mahinpei Justin Clark Isaac Lage Finale Doshi-Velez Weiwei Pan 31 91 0 24 Jun 2021
Learning Robust Latent Representations for Controllable Speech Synthesis Shakti Kumar Jithin Pradeep Hussain Zaidi DRL 30 6 0 10 May 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
3DMolNet: A Generative Network for Molecular Structures V. Nesterov Mario Wieser Volker Roth AI4CE 173 33 0 08 Oct 2020
MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network Yi Wei Zhe Gan Wenbo Li Siwei Lyu Ming-Ching Chang Lefei Zhang Jianfeng Gao Pengchuan Zhang GAN CVBM 27 18 0 03 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations Markos Georgopoulos Grigorios G. Chrysos M. Pantic Yannis Panagakis GAN DRL 19 19 0 09 Sep 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 27 25 0 14 Jul 2020
Warwick Electron Microscopy Datasets Jeffrey M. Ede 22 14 0 02 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Study of Deep Generative Models for Inorganic Chemical Compositions Yoshihide Sawada Koji Morikawa Mikiya Fujii GAN 20 13 0 25 Oct 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 42 136 0 22 Oct 2019
High Mutual Information in Representation Learning with Symmetric Variational Inference M. Livne Kevin Swersky David J. Fleet SSL DRL 33 0 0 04 Oct 2019
DualDis: Dual-Branch Disentangling with Adversarial Learning Thomas Robert Nicolas Thome Matthieu Cord CoGe DRL 25 4 0 03 Jun 2019
DIVA: Domain Invariant Variational Autoencoders Maximilian Ilse Jakub M. Tomczak Christos Louizos Max Welling DRL OOD 28 198 0 24 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 29 123 0 03 May 2019