Zobrazeno 1 - 10
of 170
pro vyhledávání: '"Besserve, P"'
Unmeasured confounding is a major challenge for identifying causal relationships from non-experimental data. Here, we propose a method that can accommodate unmeasured discrete confounding. Extending recent identifiability results in deep latent varia
Externí odkaz:
http://arxiv.org/abs/2408.05647
Assemblies of strongly interacting fermions, whether in a condensed-matter or a quantum chemistry context, range amongst the most promising candidate systems for which quantum computing platforms could provide an advantage. Near-term quantum state pr
Externí odkaz:
http://arxiv.org/abs/2406.14170
Autor:
Ghosh, Shubhangi, Gresele, Luigi, von Kügelgen, Julius, Besserve, Michel, Schölkopf, Bernhard
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 orthogonal columns. As typical in ICA, previous work focused on the c
Externí odkaz:
http://arxiv.org/abs/2312.13438
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, deciphering the causes behind phenomena in high-dimensional spaces of
Externí odkaz:
http://arxiv.org/abs/2311.18639
Autor:
von Kügelgen, Julius, Besserve, Michel, Wendong, Liang, Gresele, Luigi, Kekić, Armin, Bareinboim, Elias, Blei, David M., Schölkopf, Bernhard
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 on weak supervision, in the form of counterfactual pre- and post-inte
Externí odkaz:
http://arxiv.org/abs/2306.00542
A site-site interaction model is proposed for water in two-dimension, as an alternative to the traditional Mercedes-Benz model. In MB model, water molecules are modeled as 2-dimensional Lennard-Jones disks with three hydrogen bonding arms arranged sy
Externí odkaz:
http://arxiv.org/abs/2306.00907
Autor:
Wendong, Liang, Kekić, Armin, von Kügelgen, Julius, Buchholz, Simon, Besserve, Michel, Gresele, Luigi, Schölkopf, Bernhard
Independent Component Analysis (ICA) aims to recover independent latent variables from observed mixtures thereof. Causal Representation Learning (CRL) aims instead to infer causally related (thus often statistically dependent) latent variables, toget
Externí odkaz:
http://arxiv.org/abs/2305.17225
Quantum computing technologies are making steady progress. This has opened new opportunities for tackling problems whose complexity prevents their description on classical computers. A prototypical example of these complex problems are interacting qu
Externí odkaz:
http://arxiv.org/abs/2303.04850
Transient phenomena play a key role in coordinating brain activity at multiple scales, however,their underlying mechanisms remain largely unknown. A key challenge for neural data science is thus to characterize the network interactions at play during
Externí odkaz:
http://arxiv.org/abs/2209.07508
Publikováno v:
NeurIPS 2022
Unsupervised learning of latent variable models (LVMs) is widely used to represent data in machine learning. When such models reflect the ground truth factors and the mechanisms mapping them to observations, there is reason to expect that they allow
Externí odkaz:
http://arxiv.org/abs/2208.06406