Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

9 February 2021

Finale Doshi-Velez

Papers citing "Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement"

8 / 8 papers shown

Title
Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models Baao Xie Qiuyu Chen Yunnan Wang Zequn Zhang Xin Jin Wenjun Zeng OffRL 36 2 0 26 Jul 2024
Learning Discrete Concepts in Latent Hierarchical Models Lingjing Kong Guan-Hong Chen Biwei Huang Eric P. Xing Yuejie Chi Kun Zhang 52 4 0 01 Jun 2024
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 35 78 0 21 Nov 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation Thien Q. Tran Kazuto Fukuchi Youhei Akimoto Jun Sakuma CML 40 10 0 09 Sep 2021
Evaluating the Interpretability of Generative Models by Interactive Reconstruction A. Ross Nina Chen Elisa Zhao Hang Elena L. Glassman Finale Doshi-Velez 103 49 0 02 Feb 2021
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 181 313 0 07 Feb 2020
Building machines that adapt and compute like brains Brenden Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 890 0 11 Nov 2017