
Sign up to save your podcasts
Or


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.
By Sam Charrington4.7
422422 ratings
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.

1,109 Listeners

168 Listeners

307 Listeners

345 Listeners

233 Listeners

209 Listeners

204 Listeners

313 Listeners

101 Listeners

554 Listeners

146 Listeners

103 Listeners

229 Listeners

688 Listeners

34 Listeners