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M. Besserve

27 papers hereh-index 171.4k citations56 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author14
  • last author10

Across the 27 of 27 papers where every author was matched, so the position is known.

fields
  • stat.ML13
  • cs.LG6
  • q-bio.NC2
  • stat.ME2
  • cs.AI1
  • cs.GT1
same name
  • M. Besserve — 5 papers, h 13
  • M. Besserve — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20122026
most citedSelf-Supervised Learning with Data Augmentations Provably Isolates Content from Style

62 citations · 125 across the 26 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

stat.ML2023

Independent Mechanism Analysis and the Manifold Hypothesis

Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen +2

Independent Mechanism Analysis (IMA) seeks to address non-identifiability in nonlinear Independent Component Analysis (ICA) by assuming that the Jacobian of the mixing function has…

stat.ML2023

Targeted Reduction of Causal Models

Armin Kekić, Bernhard Schölkopf, Michel Besserve

Why does a phenomenon occur? Addressing this question is central to most scientific inquiries and often relies on simulations of scientific models. As models become more intricate,…

stat.ML2023★ 2 cited

Nonparametric Identifiability of Causal Representations from Unknown Interventions

Julius von Kügelgen, Michel Besserve, Liang Wendong +5

We study causal representation learning, the task of inferring latent causal variables and their causal relations from high-dimensional mixtures of the variables. Prior work relies…

stat.ML2023★ 2 cited

Causal Component Analysis

Liang Wendong, Armin Kekić, Julius von Kügelgen +4

Independent Component Analysis (ICA) aims to recover independent latent variables from observed mixtures thereof. Causal Representation Learning (CRL) aims instead to infer causall…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.