Zobrazeno 1 - 10
of 8 435
pro vyhledávání: '"P. Färber"'
Autor:
Anderson, L. D., Camilo, F., Faerber, Timothy, Bietenholz, M., Bordiu, C., Bufano, F., Chibueze, J. O., Cotton, W. D., Ingallinera, A., Loru, S., Rigby, A., Riggi, S., Thompson, M. A., Trigilio, C., Umana, G., Williams, G. M.
Context. Sensitive radio continuum data could remove the difference between the number of known supernova remnants (SNRs) in the Galaxy compared to that expected, but due to confusion in the Galactic plane, faint SNRs can be challenging to distinguis
Externí odkaz:
http://arxiv.org/abs/2409.16607
Autor:
Susanti, Yuni, Färber, Michael
Causal discovery aims to estimate causal structures among variables based on observational data. Large Language Models (LLMs) offer a fresh perspective to tackle the causal discovery problem by reasoning on the metadata associated with variables rath
Externí odkaz:
http://arxiv.org/abs/2407.18752
In this paper, we introduce AutoRDF2GML, a framework designed to convert RDF data into data representations tailored for graph machine learning tasks. AutoRDF2GML enables, for the first time, the creation of both content-based features -- i.e., featu
Externí odkaz:
http://arxiv.org/abs/2407.18735
We introduce ComplexTempQA,a large-scale dataset consisting of over 100 million question-answer pairs designed to tackle the challenges in temporal question answering. ComplexTempQA significantly surpasses existing benchmarks like HOTPOTQA, TORQUE, a
Externí odkaz:
http://arxiv.org/abs/2406.04866
Autor:
Shao, Chen, Giacoumidis, Elias, Matalla, Patrick, Li, Jialei, Li, Shi, Randel, Sebastian, Richter, Andre, Faerber, Michael, Kaefer, Tobias
We experimentally demonstrate a novel, low-complexity Fourier Convolution-based Network (FConvNet) based equalizer for 112 Gb/s upstream PAM4-PON. At a BER of 0.005, FConvNet enhances the receiver sensitivity by 2 and 1 dB compared to a 51-tap Sato e
Externí odkaz:
http://arxiv.org/abs/2405.02609
Autor:
Shao, Chen, Giacoumidis, Elias, Billah, Syed Moktacim, Li, Shi, Li, Jialei, Sahu, Prashasti, Richter, Andre, Kaefer, Tobias, Faerber, Michael
In recent years, extensive research has been conducted to explore the utilization of machine learning algorithms in various direct-detected and self-coherent short-reach communication applications. These applications encompass a wide range of tasks,
Externí odkaz:
http://arxiv.org/abs/2405.09557
Autor:
Shao, Chen, Giacoumidis, Elias, Li, Shi, Li, Jialei, Faerber, Michael, Kaefer, Tobias, Richter, Andre
A frequency-calibrated SCINet (FC-SCINet) equalizer is proposed for down-stream 100G PON with 28.7 dB path loss. At 5 km, FC-SCINet improves the BER by 88.87% compared to FFE and a 3-layer DNN with 10.57% lower complexity.
Comment: 3 pages, 6 fi
Comment: 3 pages, 6 fi
Externí odkaz:
http://arxiv.org/abs/2405.00720
Autor:
Yuan, Shuzhou, Färber, Michael
Pretrained Language Models (PLMs) benefit from external knowledge stored in graph structures for various downstream tasks. However, bridging the modality gap between graph structures and text remains a significant challenge. Traditional methods like
Externí odkaz:
http://arxiv.org/abs/2404.06911
Local interactions drive emergent collective behavior, which pervades biological and social complex systems. But uncovering the interactions that produce a desired behavior remains a core challenge. In this paper, we present EvoSOPS, an evolutionary
Externí odkaz:
http://arxiv.org/abs/2404.05915
Autor:
Färber, Michael
jq is a widely used tool that provides a programming language to manipulate JSON data. However, the jq language is currently only specified by its implementation, making it difficult to reason about its behaviour. To this end, we provide a formal syn
Externí odkaz:
http://arxiv.org/abs/2403.20132