Enriching Disentanglement: From Logical Definitions to Quantitative Metrics

19 May 2023

Papers citing "Enriching Disentanglement: From Logical Definitions to Quantitative Metrics"

30 / 30 papers shown

Title
Geometric Algebra Transformer Johann Brehmer P. D. Haan S. Behrends Taco S. Cohen 61 30 0 28 May 2023
A Category-theoretical Meta-analysis of Definitions of Disentanglement Yivan Zhang Masashi Sugiyama 90 3 0 11 May 2023
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 48 33 0 13 Oct 2022
Homomorphism Autoencoder -- Learning Group Structured Representations from Observed Transitions Hamza Keurti Hsiao-Ru Pan M. Besserve Benjamin Grewe Bernhard Schölkopf AI4CE 36 15 0 25 Jul 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 53 45 0 01 Apr 2022
Weakly supervised causal representation learning Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 57 129 0 30 Mar 2022
Graph Neural Networks are Dynamic Programmers Andrew Dudzik Petar Velickovic 73 64 0 29 Mar 2022
Multi-Agent MDP Homomorphic Networks Elise van der Pol H. V. Hoof F. Oliehoek Max Welling AI4CE 64 30 0 09 Oct 2021
Measuring Disentanglement: A Review of Metrics M. Carbonneau Julian Zaïdi Jonathan Boilard G. Gagnon CoGe DRL 49 84 0 16 Dec 2020
A Survey on Contrastive Self-supervised Learning Ashish Jaiswal Ashwin Ramesh Babu Mohammad Zaki Zadeh Debapriya Banerjee F. Makedon SSL 112 1,385 0 31 Oct 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 91 82 0 27 Oct 2020
Linear Disentangled Representations and Unsupervised Action Estimation Matthew Painter Jonathon S. Hare Adam Prugel-Bennett CoGe DRL 64 20 0 18 Aug 2020
Natural Graph Networks P. D. Haan Taco S. Cohen Max Welling GNN 52 44 0 16 Jul 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 127 14,883 0 18 Jun 2020
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology Sharon Zhou E. Zelikman F. Lu A. Ng Gunnar Carlsson Stefano Ermon DRL 42 27 0 05 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 63 46 0 28 May 2020
A Metric Learning Reality Check Kevin Musgrave Serge J. Belongie Ser-Nam Lim 132 476 0 18 Mar 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
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 95 651 0 31 Dec 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 106 137 0 22 Oct 2019
A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics Tobias Fritz 43 183 0 19 Aug 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset Muhammad Waleed Gondal Manuel Wüthrich Ðorðe Miladinovic Francesco Locatello M. Breidt V. Volchkov J. Akpo Olivier Bachem Bernhard Schölkopf Stefan Bauer OOD DRL 79 138 0 07 Jun 2019
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments Hugo Caselles-Dupré Michael Garcia Ortiz David Filliat DRL 51 66 0 30 Mar 2019
Towards a Definition of Disentangled Representations I. Higgins David Amos David Pfau S. Racanière Loic Matthey Danilo Jimenez Rezende Alexander Lerchner OCL DRL 92 480 0 05 Dec 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
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 62 1,346 0 16 Feb 2018
Learning Deep Disentangled Embeddings with the F-Statistic Loss Karl Ridgeway Michael C. Mozer FedML DRL CoGe 54 218 0 14 Feb 2018
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 269 619 0 22 Sep 2016
Transformation Properties of Learned Visual Representations Taco S. Cohen Max Welling 47 106 0 24 Dec 2014
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 220 12,422 0 24 Jun 2012