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UID:198@isdm.umontpellier.fr
DTSTART;TZID=Europe/Paris:20251009T140000
DTEND;TZID=Europe/Paris:20251009T140000
DTSTAMP:20260825T131817Z
URL:https://isdm.umontpellier.fr/events/what-is-a-good-matching-of-probabi
 lity-measures-a-counterfactual-lens-on-transport-maps/
SUMMARY:What is a good matching of probability measures? A counterfactual l
 ens on transport maps
DESCRIPTION:Room 03.124\, Building 5\, St Priest campus\n\nMachine Learning
  in Montpellier\, Theory &amp\; Practice - Luca Ganassali (Univ. Paris-Sac
 lay)\n\nCoupling probability measures is central to statistics and machine
  learning\, yet transport maps are generally non-unique. The common recour
 se to optimal transport\, motivated by cost minimization and cyclical mono
 tonicity\, obscures the fact that several distinct notions of multivariate
  monotone matchings coexist. In this talk\, we will first compare three co
 nstructions of transport maps—cyclically monotone\, quantile-preserving\
 , and triangular maps—characterizing when they coincide and highlighting
  their structural properties. We will then connect this analysis to causal
  inference\, showing how counterfactual reasoning can be framed as selecti
 ng a transport map and when causal assumptions align with classical statis
 tical transports. Taken together\, these results aim to enrich the theoret
 ical understanding of families of transport maps and to clarify their poss
 ible causal interpretations. This talk is based on joint work with Lucas D
 e Lara.\n\nMachine Learning in Montpellier\, Theory &amp\; Practice
ATTACH;FMTTYPE=image/jpeg:https://isdm.umontpellier.fr/wp-content/uploads/
 2026/06/ml-mtp-gC78d5.png
CATEGORIES:ML MTP
LOCATION:Room 03.124\, Building 5\, St Priest Campus\, Montpellier\, 34000\
 , France
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