Causal Representation Learning

Add to your list(s) Download to your calendar using vCal

• Chaochao Lu, University of Cambridge
• Wednesday 10 March 2021, 11:00-12:30
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09.

If you have a question about this talk, please contact Elre Oldewage.

In recent years, there is growing interest in integrating machine learning with causality, as both communities are realising that one can benefit from the advances of the other. In this talk, we first review fundamental concepts of causal inference in relation to key problems of machine learning to show how causality can contribute to machine learning. Then, since most work in causality is predicated on that causal variables are given, we discuss how to discover high-level causal variables from low-level observations by leveraging machine learning methods, which is a central problem for causality and AI. Finally, we showcase a series of recent work on designing practical algorithms to address this problem.

References: [1] Schölkopf et al. Towards Causal Representation Learning. 2021 [2] Peters et al. Causal Inference using Invariant Prediction: Identification and Confidence Intervals. 2015 [3] Arjovsky et al. Invariant Risk Minimization. 2019 [4] Lu et al. Nonlinear Invariant Risk Minimization: A Causal Approach. 2021

This talk is part of the Machine Learning Reading Group @ CUED series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Computational Continuum Mechanics Group Seminars
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Journal Clubs
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• ML
• Machine Learning Reading Group
• Machine Learning Reading Group @ CUED
• Machine Learning Summary
• Quantum Matter Journal Club
• Required lists for MLG
• School of Technology
• Simon Baker's List
• TQS Journal Clubs
• Trust & Technology Initiative - interesting events
• bld31
• custom
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09
• ndk22's list
• ob366-ai4er
• rp587
• yk373's list

Note that ex-directory lists are not shown.