Zobrazeno 1 - 10
of 24 328
pro vyhledávání: '"Thaler, A."'
Autor:
Wang, Ze, Wu, Zekun, Guan, Xin, Thaler, Michael, Koshiyama, Adriano, Lu, Skylar, Beepath, Sachin, Ertekin Jr., Ediz, Perez-Ortiz, Maria
This paper presents a novel framework for benchmarking hierarchical gender hiring bias in Large Language Models (LLMs) for resume scoring, revealing significant issues of reverse bias and overdebiasing. Our contributions are fourfold: First, we intro
Externí odkaz:
http://arxiv.org/abs/2406.15484
Extracting scientific understanding from particle-physics experiments requires solving diverse learning problems with high precision and good data efficiency. We propose the Lorentz Geometric Algebra Transformer (L-GATr), a new multi-purpose architec
Externí odkaz:
http://arxiv.org/abs/2405.14806
Publikováno v:
Oceanography, 2024 Jun 01. 37(2), 167-173.
Externí odkaz:
https://www.jstor.org/stable/27309832
Autor:
Arnold, Robert, Prassl, Anton J., Neic, Aurel, Thaler, Franz, Augustin, Christoph M., Gsell, Matthias A. F., Gillette, Karli, Manninger, Martin, Scherr, Daniel, Plank, Gernot
Background and Objective: Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific calibration of digital twin models. However, data exported from commerc
Externí odkaz:
http://arxiv.org/abs/2403.10394
Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose "Moment Pooling", a natural extension of Deep Sets networks which drast
Externí odkaz:
http://arxiv.org/abs/2403.08854
We present PAPERCLIP (Proposal Abstracts Provide an Effective Representation for Contrastive Language-Image Pre-training), a method which associates astronomical observations imaged by telescopes with natural language using a neural network model. Th
Externí odkaz:
http://arxiv.org/abs/2403.08851
A graph is $k$-vertex-critical if $\chi(G)=k$ but $\chi(G-v)
Externí odkaz:
http://arxiv.org/abs/2402.15908
Autor:
Thaler, Denny, Dhulipala, Somayajulu L. N., Bamer, Franz, Markert, Bernd, Shields, Michael D.
We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampling of the Hamiltonian Monte Carlo method with computationally efficien
Externí odkaz:
http://arxiv.org/abs/2401.05244
Late gadolinium enhanced (LGE) magnetic resonance (MR) imaging is widely established to assess the viability of myocardial tissue of patients after acute myocardial infarction (MI). We propose the Cascading Refinement CNN (CaRe-CNN), which is a fully
Externí odkaz:
http://arxiv.org/abs/2312.11315
Autor:
Chen, Yu-Chen, Chen, Yi, Badea, Anthony, Baty, Austin, Innocenti, Gian Michele, Maggi, Marcello, McGinn, Christopher, Peters, Michael, Sheng, Tzu-An, Thaler, Jesse, Lee, Yen-Jie
The first measurement of two-particle angular correlations for charged particles produced in $e^+e^-$ annihilation up to $\sqrt{s} = 209$ GeV with LEP-II data is presented. Hadronic $e^+e^-$ data, archived at center-of-mass energies ranging from 183
Externí odkaz:
http://arxiv.org/abs/2312.05084