Zobrazeno 1 - 10
of 2 833
pro vyhledávání: '"Dhanya, P."'
Autor:
Brouillard, Philippe, Squires, Chandler, Wahl, Jonas, Kording, Konrad P., Sachs, Karen, Drouin, Alexandre, Sridhar, Dhanya
Causal discovery aims to automatically uncover causal relationships from data, a capability with significant potential across many scientific disciplines. However, its real-world applications remain limited. Current methods often rely on unrealistic
Externí odkaz:
http://arxiv.org/abs/2412.01953
In this article, we examine the H\"older regularity of solutions to equations involving a mixed local-nonlocal nonlinear nonhomogeneous operator $(-\Delta)_{p} + (-\Delta)_{q}^{s}$, under the minimal assumption that $p> sq$. The regularity result is
Externí odkaz:
http://arxiv.org/abs/2411.18505
Given two sets of elements (such as cell types and drug compounds), researchers typically only have access to a limited subset of their interactions. The task of causal imputation involves using this subset to predict unobserved interactions. Squires
Externí odkaz:
http://arxiv.org/abs/2410.20647
All four invariants of the mutual-visibility problem and, all four invariants of the general position problem are determined for glued binary trees. The number of the corresponding extremal sets is obtained in each of the eight situations. The result
Externí odkaz:
http://arxiv.org/abs/2410.17611
Autor:
Elmoznino, Eric, Marty, Tom, Kasetty, Tejas, Gagnon, Leo, Mittal, Sarthak, Fathi, Mahan, Sridhar, Dhanya, Lajoie, Guillaume
A central goal of machine learning is generalization. While the No Free Lunch Theorem states that we cannot obtain theoretical guarantees for generalization without further assumptions, in practice we observe that simple models which explain the trai
Externí odkaz:
http://arxiv.org/abs/2410.14086
Autor:
Brouillard, Philippe, Lachapelle, Sébastien, Kaltenborn, Julia, Gurwicz, Yaniv, Sridhar, Dhanya, Drouin, Alexandre, Nowack, Peer, Runge, Jakob, Rolnick, David
Scientific research often seeks to understand the causal structure underlying high-level variables in a system. For example, climate scientists study how phenomena, such as El Ni\~no, affect other climate processes at remote locations across the glob
Externí odkaz:
http://arxiv.org/abs/2410.07013
Autor:
Nair, Dhanya G., Morganti, Raffaella, Brienza, Marisa, Mingo, Beatriz, Croston, Judith H., Jurlin, Nika, Shimwell, Timothy W., Callingham, Joseph R., Hardcastle, Martin J.
Publikováno v:
A&A 691, A287 (2024)
(abridged) Characterizing duty cycles of recurrent phases of dormancy and activity in supermassive black holes in active galactic nuclei is crucial in understanding impact of energy released on host galaxies and their evolution. However, identifying
Externí odkaz:
http://arxiv.org/abs/2409.15587
In this article, we deal with the fine boundary regularity, a weighted H\"{o}lder regularity of weak solutions to the problem involving the fractional $(p,q)$-Laplacian denoted by \begin{eqnarray*} \begin{array}{rll} (-\Delta)_{p}^{s} u + (-\Delta)_{
Externí odkaz:
http://arxiv.org/abs/2406.07995
Many causal systems such as biological processes in cells can only be observed indirectly via measurements, such as gene expression. Causal representation learning -- the task of correctly mapping low-level observations to latent causal variables --
Externí odkaz:
http://arxiv.org/abs/2405.20482
Autor:
Mittal, Sarthak, Elmoznino, Eric, Gagnon, Leo, Bhardwaj, Sangnie, Sridhar, Dhanya, Lajoie, Guillaume
Large autoregressive models like Transformers can solve tasks through in-context learning (ICL) without learning new weights, suggesting avenues for efficiently solving new tasks. For many tasks, e.g., linear regression, the data factorizes: examples
Externí odkaz:
http://arxiv.org/abs/2405.19162