Zobrazeno 1 - 10
of 80 186
pro vyhledávání: '"Franke, A. A."'
Autor:
Rompel, Vincent, Franke, Sabrina, Kübelbäck, Florian, Oberauer, Lothar, Schweizer, Luca, Stangler, Korbinian, Steiger, Hans Th. J., Stock, Matthias Raphael, Ulrich, Andreas
Future neutrino experiments at low energies such as JUNO or THEIA will use large volume homogeneous liquid scintillator detectors. The optical attenuation length of the liquid is of uttermost importance for the successful realization of these experim
Externí odkaz:
http://arxiv.org/abs/2412.15855
Privacy-Preserving Record linkage (PPRL) is an essential component in data integration tasks of sensitive information. The linkage quality determines the usability of combined datasets and (machine learning) applications based on them. We present a n
Externí odkaz:
http://arxiv.org/abs/2412.04178
Autor:
Iliakopoulou, Nikoleta, Stojkovic, Jovan, Alverti, Chloe, Xu, Tianyin, Franke, Hubertus, Torrellas, Josep
The widespread adoption of LLMs has driven an exponential rise in their deployment, imposing substantial demands on inference clusters. These clusters must handle numerous concurrent queries for different LLM downstream tasks. To handle multi-task se
Externí odkaz:
http://arxiv.org/abs/2411.17741
Autor:
Chen, Deming, Youssef, Alaa, Pendse, Ruchi, Schleife, André, Clark, Bryan K., Hamann, Hendrik, He, Jingrui, Laino, Teodoro, Varshney, Lav, Wang, Yuxiong, Sil, Avirup, Jabbarvand, Reyhaneh, Xu, Tianyin, Kindratenko, Volodymyr, Costa, Carlos, Adve, Sarita, Mendis, Charith, Zhang, Minjia, Núñez-Corrales, Santiago, Ganti, Raghu, Srivatsa, Mudhakar, Kim, Nam Sung, Torrellas, Josep, Huang, Jian, Seelam, Seetharami, Nahrstedt, Klara, Abdelzaher, Tarek, Eilam, Tamar, Zhao, Huimin, Manica, Matteo, Iyer, Ravishankar, Hirzel, Martin, Adve, Vikram, Marinov, Darko, Franke, Hubertus, Tong, Hanghang, Ainsworth, Elizabeth, Zhao, Han, Vasisht, Deepak, Do, Minh, Oliveira, Fabio, Pacifici, Giovanni, Puri, Ruchir, Nagpurkar, Priya
This white paper, developed through close collaboration between IBM Research and UIUC researchers within the IIDAI Institute, envisions transforming hybrid cloud systems to meet the growing complexity of AI workloads through innovative, full-stack co
Externí odkaz:
http://arxiv.org/abs/2411.13239
Autor:
Grazzi, Riccardo, Siems, Julien, Franke, Jörg K. H., Zela, Arber, Hutter, Frank, Pontil, Massimiliano
Linear Recurrent Neural Networks (LRNNs) such as Mamba, RWKV, GLA, mLSTM, and DeltaNet have emerged as efficient alternatives to Transformers in large language modeling, offering linear scaling with sequence length and improved training efficiency. H
Externí odkaz:
http://arxiv.org/abs/2411.12537
Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs associated with real-world data collection. However, leveraging synthetic data generated via game eng
Externí odkaz:
http://arxiv.org/abs/2411.05633
Autor:
Strangmann, Tobias, Purucker, Lennart, Franke, Jörg K. H., Rapant, Ivo, Ferreira, Fabio, Hutter, Frank
As the landscape of large language models expands, efficiently finetuning for specific tasks becomes increasingly crucial. At the same time, the landscape of parameter-efficient finetuning methods rapidly expands. Consequently, practitioners face a m
Externí odkaz:
http://arxiv.org/abs/2411.01195
Perceiving the environment via cameras is crucial for Reinforcement Learning (RL) in robotics. While images are a convenient form of representation, they often complicate extracting important geometric details, especially with varying geometries or d
Externí odkaz:
http://arxiv.org/abs/2410.18800
Recent advances in novel view synthesis (NVS), particularly neural radiance fields (NeRF) and Gaussian splatting (3DGS), have demonstrated impressive results in photorealistic scene rendering. These techniques hold great potential for applications in
Externí odkaz:
http://arxiv.org/abs/2410.17932
Autor:
Hahlbohm, Florian, Friederichs, Fabian, Weyrich, Tim, Franke, Linus, Kappel, Moritz, Castillo, Susana, Stamminger, Marc, Eisemann, Martin, Magnor, Marcus
3D Gaussian Splats (3DGS) have proven a versatile rendering primitive, both for inverse rendering as well as real-time exploration of scenes. In these applications, coherence across camera frames and multiple views is crucial, be it for robust conver
Externí odkaz:
http://arxiv.org/abs/2410.08129