The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Weakly Supervised Causal Representation Learning with Johann Brehmer - #605
15 Dec 2022
Today we’re excited to kick off our coverage of the 2022 NeurIPS conference with Johann Brehmer, a research scientist at Qualcomm AI Research in Amsterdam. We begin our conversation discussing some of the broader problems that causality will help us solve, before turning our focus to Johann’s paper Weakly supervised causal representation learning, which seeks to prove that high-level causal representations are identifiable in weakly supervised settings. We also discuss a few other papers that the team at Qualcomm presented, including neural topological ordering for computation graphs, as well as some of the demos they showcased, which we’ll link to on the show notes page. The complete show notes for this episode can be found at twimlai.com/go/605.
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
Dr. Erich G. Anderer, Chief of the Division of Neurosurgery and Surgical Director of Perioperative Services at NYU Langone Hospital–Brooklyn
09 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
Dr. Nolan Wessell, Assistant Professor and Well-being Co-Director, Department of Orthopedic Surgery, Division of Spine Surgery, University of Colorado School of Medicine
08 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
NPR News: 12-08-2025 2AM EST
08 Dec 2025
NPR News Now
NPR News: 12-08-2025 1AM EST
08 Dec 2025
NPR News Now