Zobrazeno 1 - 10
of 12 132
pro vyhledávání: '"P. Wasserman"'
Autor:
Wasserman, Max, Mateos, Gonzalo
Graphs serve as generic tools to encode the underlying relational structure of data. Often this graph is not given, and so the task of inferring it from nodal observations becomes important. Traditional approaches formulate a convex inverse problem w
Externí odkaz:
http://arxiv.org/abs/2406.14786
Image-to-fMRI encoding is important for both neuroscience research and practical applications. However, such "Brain-Encoders" have been typically trained per-subject and per fMRI-dataset, thus restricted to very limited training data. In this paper w
Externí odkaz:
http://arxiv.org/abs/2406.12179
Autor:
De Smet, Maxim, Matsumoto, Yuta, Zwerver, Anne-Marije J., Tryputen, Larysa, de Snoo, Sander L., Amitonov, Sergey V., Sammak, Amir, Samkharadze, Nodar, Gül, Önder, Wasserman, Rick N. M., Rimbach-Russ, Maximilian, Scappucci, Giordano, Vandersypen, Lieven M. K.
The computational power and fault-tolerance of future large-scale quantum processors derive in large part from the connectivity between the qubits. One approach to increase connectivity is to engineer qubit-qubit interactions at a distance. Alternati
Externí odkaz:
http://arxiv.org/abs/2406.07267
Autor:
Wade, Richard D., Wasserman, Thomas A.
We explain how Cohen--Macaulay classifying spaces are ubiquitous among discrete groups that satisfy Bieri--Eckmann duality, and compare Bieri--Eckmann duality to duality results for Cohen--Macaulay complexes. We use this comparison to give a descript
Externí odkaz:
http://arxiv.org/abs/2405.05881
Autor:
Wade, Richard D., Wasserman, Thomas A.
We prove a duality theorem for Cohen--Macaulay simplicial complexes. This is a generalisation of Poincar\'e Duality, framed in the language of combinatorial sheaves. Our treatment is self-contained and accessible for readers with a working knowledge
Externí odkaz:
http://arxiv.org/abs/2405.05873
Image editing has advanced significantly with the introduction of text-conditioned diffusion models. Despite this progress, seamlessly adding objects to images based on textual instructions without requiring user-provided input masks remains a challe
Externí odkaz:
http://arxiv.org/abs/2404.18212
Autor:
Cousins, Robert D., Wasserman, Larry
This is a writeup, with some elaboration, of the talks by the two authors (a physicist and a statistician) at the first PHYSTAT Informal review on January 24, 2024. We discuss Bayesian and frequentist approaches to dealing with nuisance parameters, i
Externí odkaz:
http://arxiv.org/abs/2404.17180
Combining Functional MRI (fMRI) data across different subjects and datasets is crucial for many neuroscience tasks. Relying solely on shared anatomy for brain-to-brain mapping is inadequate. Existing functional transformation methods thus depend on s
Externí odkaz:
http://arxiv.org/abs/2404.11143
With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene expression levels
Externí odkaz:
http://arxiv.org/abs/2404.09119
Doubly robust estimators with cross-fitting have gained popularity in causal inference due to their favorable structure-agnostic error guarantees. However, when additional structure, such as H\"{o}lder smoothness, is available then more accurate "dou
Externí odkaz:
http://arxiv.org/abs/2403.15175