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Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations

4 December 2021

Papers citing "Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations"

50 / 54 papers shown

Title
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 74 81 0 04 Nov 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lio Marco Maggini S. Melacci 77 69 0 11 Aug 2021
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation Marius Memmel Camila González Anirban Mukhopadhyay CLL OOD MedIm 42 18 0 19 Jul 2021
Prototype Guided Federated Learning of Visual Feature Representations Umberto Michieli Mete Ozay FedML 65 38 0 19 May 2021
Weakly Supervised Multi-task Learning for Concept-based Explainability Catarina Belém Vladimir Balayan Pedro Saleiro P. Bizarro 118 10 0 26 Apr 2021
Where and What? Examining Interpretable Disentangled Representations Xinqi Zhu Chang Xu Dacheng Tao FAtt DRL 79 39 0 07 Apr 2021
An Empirical Study of Training Self-Supervised Vision Transformers Xinlei Chen Saining Xie Kaiming He ViT 157 1,868 0 05 Apr 2021
Evaluating the Interpretability of Generative Models by Interactive Reconstruction A. Ross Nina Chen Elisa Zhao Hang Elena L. Glassman Finale Doshi-Velez 139 49 0 02 Feb 2021
Measuring Disentanglement: A Review of Metrics M. Carbonneau Julian Zaïdi Jonathan Boilard G. Gagnon CoGe DRL 63 84 0 16 Dec 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 76 110 0 25 Nov 2020
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields Michael Niemeyer Andreas Geiger OCL 156 963 0 24 Nov 2020
Exploring Simple Siamese Representation Learning Xinlei Chen Kaiming He SSL 258 4,067 0 20 Nov 2020
Multimodal Prototypical Networks for Few-shot Learning Frederik Pahde M. Puscas T. Klein Moin Nabi 59 90 0 17 Nov 2020
Disentangling 3D Prototypical Networks For Few-Shot Concept Learning Mihir Prabhudesai Shamit Lal Darshan Patil H. Tung Adam W. Harley Katerina Fragkiadaki OCL 3DV 3DPC 102 20 0 06 Nov 2020
Contextual Semantic Interpretability Diego Marcos Ruth C. Fong Sylvain Lobry Rémi Flamary Nicolas Courty D. Tuia SSL 106 28 0 18 Sep 2020
Concept Bottleneck Models Pang Wei Koh Thao Nguyen Y. S. Tang Stephen Mussmann Emma Pierson Been Kim Percy Liang 99 828 0 09 Jul 2020
Object-Centric Learning with Slot Attention Francesco Locatello Dirk Weissenborn Thomas Unterthiner Aravindh Mahendran G. Heigold Jakob Uszkoreit Alexey Dosovitskiy Thomas Kipf OCL 225 856 0 26 Jun 2020
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments Mathilde Caron Ishan Misra Julien Mairal Priya Goyal Piotr Bojanowski Armand Joulin OCL SSL 246 4,097 0 17 Jun 2020
Self-Supervised Relational Reasoning for Representation Learning Massimiliano Patacchiola Amos Storkey OOD SSL 55 63 0 10 Jun 2020
End-to-End Object Detection with Transformers Nicolas Carion Francisco Massa Gabriel Synnaeve Nicolas Usunier Alexander Kirillov Sergey Zagoruyko ViT 3DV PINN 424 13,094 0 26 May 2020
Adversarial Continual Learning Sayna Ebrahimi Franziska Meier Roberto Calandra Trevor Darrell Marcus Rohrbach CLL VLM 195 200 0 21 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 375 18,859 0 13 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 240 319 0 07 Feb 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 104 213 0 15 Jan 2020
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition Zhixuan Lin Yi-Fu Wu Skand Peri Weihao Sun Gautam Singh Fei Deng Jindong Jiang Sungjin Ahn BDL OCL 3DPC 168 250 0 08 Jan 2020
Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement M. Vowels Necati Cihan Camgöz Richard Bowden CoGe DRL 47 9 0 15 Nov 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 122 139 0 22 Oct 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan O. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 233 306 0 17 Oct 2019
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations Martin Engelcke Adam R. Kosiorek Oiwi Parker Jones Ingmar Posner OCL 124 307 0 30 Jul 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 106 509 0 01 Mar 2019
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded Ramprasaath R. Selvaraju Stefan Lee Yilin Shen Hongxia Jin Shalini Ghosh Larry Heck Dhruv Batra Devi Parikh FAtt VLM 64 254 0 11 Feb 2019
MONet: Unsupervised Scene Decomposition and Representation Christopher P. Burgess Loic Matthey Nicholas Watters Rishabh Kabra I. Higgins M. Botvinick Alexander Lerchner OCL 88 529 0 22 Jan 2019
Recent Advances in Autoencoder-Based Representation Learning Michael Tschannen Olivier Bachem Mario Lucic OOD SSL DRL 72 445 0 12 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 124 1,471 0 29 Nov 2018
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding Kexin Yi Jiajun Wu Chuang Gan Antonio Torralba Pushmeet Kohli J. Tenenbaum NAI 84 610 0 04 Oct 2018
Interpretable Latent Spaces for Learning from Demonstration Yordan V. Hristov A. Lascarides S. Ramamoorthy 42 23 0 17 Jul 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 243 1,186 0 27 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 126 946 0 20 Jun 2018
Group Normalization Yuxin Wu Kaiming He 233 3,669 0 22 Mar 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 62 1,356 0 16 Feb 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 219 1,849 0 30 Nov 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 176 591 0 13 Oct 2017
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations Diane Bouchacourt Ryota Tomioka Sebastian Nowozin BDL OOD DRL 56 313 0 24 May 2017
Mask R-CNN Kaiming He Georgia Gkioxari Piotr Dollár Ross B. Girshick ObjD 352 27,230 0 20 Mar 2017
Prototypical Networks for Few-shot Learning Jake C. Snell Kevin Swersky R. Zemel 303 8,145 0 15 Mar 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 126 591 0 10 Mar 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 344 5,372 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 196 2,538 0 02 Nov 2016
Learning without Forgetting Zhizhong Li Derek Hoiem CLL OOD SSL 304 4,423 0 29 Jun 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 159 4,237 0 12 Jun 2016