Boxhead: A Dataset for Learning Hierarchical Representations

7 October 2021

Stefan Bauer

Papers citing "Boxhead: A Dataset for Learning Hierarchical Representations"

42 / 42 papers shown

Title
Generalization and Robustness Implications in Object-Centric Learning Andrea Dittadi Samuele Papa Michele De Vita Bernhard Schölkopf Ole Winther Francesco Locatello OCL OOD 55 75 0 01 Jul 2021
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling DJordje Miladinović Aleksandar Stanić Stefan Bauer Jürgen Schmidhuber J. M. Buhmann DRL 38 9 0 16 Mar 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 100 322 0 22 Feb 2021
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement A. Ross Finale Doshi-Velez DRL 53 13 0 09 Feb 2021
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 177 350 0 20 Nov 2020
On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi Frederik Trauble Francesco Locatello M. Wuthrich Vaibhav Agrawal Ole Winther Stefan Bauer Bernhard Schölkopf OOD 88 82 0 27 Oct 2020
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 57 69 0 27 Oct 2020
Hierarchical Relational Inference Aleksandar Stanić Sjoerd van Steenkiste Jürgen Schmidhuber OCL 48 15 0 07 Oct 2020
S2RMs: Spatially Structured Recurrent Modules Nasim Rahaman Anirudh Goyal Muhammad Waleed Gondal M. Wuthrich Stefan Bauer Yash Sharma Yoshua Bengio Bernhard Schölkopf 40 14 0 13 Jul 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 67 908 0 08 Jul 2020
Learning Physical Graph Representations from Visual Scenes Daniel M. Bear Chaofei Fan Damian Mrowca Yunzhu Li S. Alter ... Jeremy Schwartz Li Fei-Fei Jiajun Wu J. Tenenbaum Daniel L. K. Yamins SSL GNN SSeg AI4CE 77 79 0 22 Jun 2020
On Disentangled Representations Learned From Correlated Data Frederik Trauble Elliot Creager Niki Kilbertus Francesco Locatello Andrea Dittadi Anirudh Goyal Bernhard Schölkopf Stefan Bauer OOD CML 59 117 0 14 Jun 2020
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image Despoina Paschalidou Luc van Gool Andreas Geiger 3DV OCL 57 108 0 02 Apr 2020
Progressive Learning and Disentanglement of Hierarchical Representations Zhiyuan Li J. Murkute P. Gyawali Linwei Wang DRL 36 40 0 24 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 220 316 0 07 Feb 2020
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 78 461 0 24 Nov 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 106 137 0 22 Oct 2019
Recurrent Independent Mechanisms Anirudh Goyal Alex Lamb Jordan Hoffmann Shagun Sodhani Sergey Levine Yoshua Bengio Bernhard Schölkopf 76 337 0 24 Sep 2019
Disentangled State Space Representations Ðorðe Miladinovic Muhammad Waleed Gondal Bernhard Schölkopf J. M. Buhmann Stefan Bauer DRL 47 30 0 07 Jun 2019
Flexibly Fair Representation Learning by Disentanglement Elliot Creager David Madras J. Jacobsen Marissa A. Weis Kevin Swersky T. Pitassi R. Zemel FaML OOD 153 333 0 06 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 64 226 0 31 May 2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning? Sjoerd van Steenkiste Francesco Locatello Jürgen Schmidhuber Olivier Bachem 74 210 0 29 May 2019
Unsupervised Discovery of Parts, Structure, and Dynamics Zhenjia Xu Zhijian Liu Chen Sun Kevin Patrick Murphy William T. Freeman J. Tenenbaum Jiajun Wu OCL 61 61 0 12 Mar 2019
Multi-Object Representation Learning with Iterative Variational Inference Klaus Greff Raphael Lopez Kaufman Rishabh Kabra Nicholas Watters Christopher P. Burgess Daniel Zoran Loic Matthey M. Botvinick Alexander Lerchner OCL SSL 98 509 0 01 Mar 2019
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling Lars Maaløe Marco Fraccaro Valentin Liévin Ole Winther BDL DRL 50 214 0 06 Feb 2019
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs Nicholas Watters Loic Matthey Christopher P. Burgess Alexander Lerchner CoGe 78 169 0 21 Jan 2019
Variational Autoencoders Pursue PCA Directions (by Accident) Michal Rolínek Dominik Zietlow Georg Martius OOD DRL 61 151 0 17 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 109 1,466 0 29 Nov 2018
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 105 162 0 31 Oct 2018
SplineNets: Continuous Neural Decision Graphs Cem Keskin Shahram Izadi 45 11 0 31 Oct 2018
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies Alessandro Achille Tom Eccles Loic Matthey Christopher P. Burgess Nicholas Watters Alexander Lerchner I. Higgins BDL 63 119 0 20 Aug 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 57 829 0 10 Apr 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 62 1,346 0 16 Feb 2018
Isolating Sources of Disentanglement in Variational Autoencoders T. Chen Xuechen Li Roger C. Grosse David Duvenaud DRL 49 447 0 14 Feb 2018
Open3D: A Modern Library for 3D Data Processing Qian-Yi Zhou Jaesik Park V. Koltun PINN AI4CE 55 1,611 0 30 Jan 2018
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations Abhishek Kumar P. Sattigeri Avinash Balakrishnan BDL DRL 76 523 0 02 Nov 2017
Causal Consistency of Structural Equation Models Paul Kishan Rubenstein S. Weichwald Stephan Bongers Joris M. Mooij Dominik Janzing Moritz Grosse-Wentrup Bernhard Schölkopf CML 75 127 0 04 Jul 2017
Poincaré Embeddings for Learning Hierarchical Representations Maximilian Nickel Douwe Kiela 79 1,301 0 22 May 2017
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 155 4,232 0 12 Jun 2016
Ladder Variational Autoencoders C. Sønderby T. Raiko Lars Maaløe Søren Kaae Sønderby Ole Winther BDL DRL 95 911 0 06 Feb 2016
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 224 8,391 0 28 Nov 2014
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 213 12,422 0 24 Jun 2012