General Identifiability and Achievability for Causal Representation Learning

24 October 2023

Papers citing "General Identifiability and Achievability for Causal Representation Learning"

6 / 6 papers shown

Title
Contextures: Representations from Contexts Runtian Zhai Kai Yang Che-Ping Tsai Burak Varici Zico Kolter Pradeep Ravikumar 119 0 0 02 May 2025
What is causal about causal models and representations? Frederik Hytting Jørgensen Luigi Gresele S. Weichwald CML 107 0 0 31 Jan 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 69 3 0 30 Oct 2024
Linear causal disentanglement via higher-order cumulants Paula Leyes Carreno Chiara Meroni A. Seigal CML 36 0 0 05 Jul 2024
Scalable Causal Discovery with Score Matching Francesco Montagna Nicoletta Noceti Lorenzo Rosasco Anton van den Hengel Francesco Locatello CML 52 25 0 06 Apr 2023
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 313 0 07 Feb 2020