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of 7 320
pro vyhledávání: '"Schöne A"'
Suicidal ideation is a serious health problem affecting millions of people worldwide. Social networks provide information about these mental health problems through users' emotional expressions. We propose a multilingual model leveraging transformer
Externí odkaz:
http://arxiv.org/abs/2412.15498
Recent years have seen a marked increase in research that aims to identify or predict risk, intention or ideation of suicide. The majority of new tasks, datasets, language models and other resources focus on English and on suicide in the context of W
Externí odkaz:
http://arxiv.org/abs/2412.15497
Autor:
Schöne, Mark, Bhisikar, Yash, Bania, Karan, Nazeer, Khaleelulla Khan, Mayr, Christian, Subramoney, Anand, Kappel, David
Handling sparse and unstructured geometric data, such as point clouds or event-based vision, is a pressing challenge in the field of machine vision. Recently, sequence models such as Transformers and state-space models entered the domain of geometric
Externí odkaz:
http://arxiv.org/abs/2411.12603
Publikováno v:
2024 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops), Kobe, Japan, 2024, pp. 76-80
The SPEC Power benchmark offers valuable insights into the energy efficiency of server systems, allowing comparisons across various hardware and software configurations. Benchmark results are publicly available for hundreds of systems from different
Externí odkaz:
http://arxiv.org/abs/2411.07062
Publikováno v:
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, FL, pages 8579-8600
The stock market provides a rich well of information that can be split across modalities, making it an ideal candidate for multimodal evaluation. Multimodal data plays an increasingly important role in the development of machine learning and has show
Externí odkaz:
http://arxiv.org/abs/2411.06616
Autor:
Mukherji, Rishav, Schöne, Mark, Nazeer, Khaleelulla Khan, Mayr, Christian, Kappel, David, Subramoney, Anand
Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs) naturally exhibit activity sparsity, and many methods exist to sparsif
Externí odkaz:
http://arxiv.org/abs/2405.00433
Autor:
Schöne, Mark, Sushma, Neeraj Mohan, Zhuge, Jingyue, Mayr, Christian, Subramoney, Anand, Kappel, David
Event-based sensors are well suited for real-time processing due to their fast response times and encoding of the sensory data as successive temporal differences. These and other valuable properties, such as a high dynamic range, are suppressed when
Externí odkaz:
http://arxiv.org/abs/2404.18508
Fatigue crack growth is usually a three-dimensional problem, but it is often simplified to two dimensions to reduce complexity. However, this study investigates the relationships between microscopic effects such as crack kinking, shear lips, and plas
Externí odkaz:
http://arxiv.org/abs/2404.01852
Autor:
Gonzalez, Hector A., Huang, Jiaxin, Kelber, Florian, Nazeer, Khaleelulla Khan, Langer, Tim, Liu, Chen, Lohrmann, Matthias, Rostami, Amirhossein, Schöne, Mark, Vogginger, Bernhard, Wunderlich, Timo C., Yan, Yexin, Akl, Mahmoud, Mayr, Christian
The joint progress of artificial neural networks (ANNs) and domain specific hardware accelerators such as GPUs and TPUs took over many domains of machine learning research. This development is accompanied by a rapid growth of the required computation
Externí odkaz:
http://arxiv.org/abs/2401.04491
Autor:
Nazeer, Khaleelulla Khan, Schöne, Mark, Mukherji, Rishav, Vogginger, Bernhard, Mayr, Christian, Kappel, David, Subramoney, Anand
As large language models continue to scale in size rapidly, so too does the computational power required to run them. Event-based networks on neuromorphic devices offer a potential way to reduce energy consumption for inference significantly. However
Externí odkaz:
http://arxiv.org/abs/2312.09084