Zobrazeno 1 - 10
of 9 640
pro vyhledávání: '"P, Matthijs"'
We study the $k$-center problem in the context of individual fairness. Let $P$ be a set of $n$ points in a metric space and $r_x$ be the distance between $x \in P$ and its $\lceil n/k \rceil$-th nearest neighbor. The problem asks to optimize the $k$-
Externí odkaz:
http://arxiv.org/abs/2412.04943
Autor:
Boelts, Jan, Deistler, Michael, Gloeckler, Manuel, Tejero-Cantero, Álvaro, Lueckmann, Jan-Matthis, Moss, Guy, Steinbach, Peter, Moreau, Thomas, Muratore, Fabio, Linhart, Julia, Durkan, Conor, Vetter, Julius, Miller, Benjamin Kurt, Herold, Maternus, Ziaeemehr, Abolfazl, Pals, Matthijs, Gruner, Theo, Bischoff, Sebastian, Krouglova, Nastya, Gao, Richard, Lappalainen, Janne K., Mucsányi, Bálint, Pei, Felix, Schulz, Auguste, Stefanidi, Zinovia, Rodrigues, Pedro, Schröder, Cornelius, Zaid, Faried Abu, Beck, Jonas, Kapoor, Jaivardhan, Greenberg, David S., Gonçalves, Pedro J., Macke, Jakob H.
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challenge. Simulation-based inference (SBI) addresses this
Externí odkaz:
http://arxiv.org/abs/2411.17337
Autor:
Bennecke, Wiebke, Oliva, Ignacio Gonzalez, Bange, Jan Philipp, Werner, Paul, Schmitt, David, Merboldt, Marco, Seiler, Anna M., Watanabe, Kenji, Taniguchi, Takashi, Steil, Daniel, Weitz, R. Thomas, Puschnig, Peter, Draxl, Claudia, Jansen, G. S. Matthijs, Reutzel, Marcel, Mathias, Stefan
Two-dimensional transition metal dichalcogenides (TMDs) and organic semiconductors (OSCs) have emerged as promising material platforms for next-generation optoelectronic devices. The combination of both is predicted to yield emergent properties while
Externí odkaz:
http://arxiv.org/abs/2411.14993
Autor:
Dong, Xin, Fu, Yonggan, Diao, Shizhe, Byeon, Wonmin, Chen, Zijia, Mahabaleshwarkar, Ameya Sunil, Liu, Shih-Yang, Van Keirsbilck, Matthijs, Chen, Min-Hung, Suhara, Yoshi, Lin, Yingyan, Kautz, Jan, Molchanov, Pavlo
We propose Hymba, a family of small language models featuring a hybrid-head parallel architecture that integrates transformer attention mechanisms with state space models (SSMs) for enhanced efficiency. Attention heads provide high-resolution recall,
Externí odkaz:
http://arxiv.org/abs/2411.13676
Image watermarking methods are not tailored to handle small watermarked areas. This restricts applications in real-world scenarios where parts of the image may come from different sources or have been edited. We introduce a deep-learning model for lo
Externí odkaz:
http://arxiv.org/abs/2411.07231
Intelligent agents designed for interactive environments face significant challenges in text-based games, a domain that demands complex reasoning and adaptability. While agents based on large language models (LLMs) using self-reflection have shown pr
Externí odkaz:
http://arxiv.org/abs/2411.02223
Understanding the nature of dark matter in the Universe is an important goal of modern cosmology. A key method for probing this distribution is via weak gravitational lensing mass-mapping - a challenging ill-posed inverse problem where one infers the
Externí odkaz:
http://arxiv.org/abs/2410.24197
Semi-supervised anomaly detection is based on the principle that potential anomalies are those records that look different from normal training data. However, in some cases we are specifically interested in anomalies that correspond to high attribute
Externí odkaz:
http://arxiv.org/abs/2410.23158
Autor:
Chen, Zhuoming, Sadhukhan, Ranajoy, Ye, Zihao, Zhou, Yang, Zhang, Jianyu, Nolte, Niklas, Tian, Yuandong, Douze, Matthijs, Bottou, Leon, Jia, Zhihao, Chen, Beidi
Large language models (LLMs) with long context windows have gained significant attention. However, the KV cache, stored to avoid re-computation, becomes a bottleneck. Various dynamic sparse or TopK-based attention approximation methods have been prop
Externí odkaz:
http://arxiv.org/abs/2410.16179
Autor:
Yang, Lincen, van Leeuwen, Matthijs
Conditional density estimation (CDE) goes beyond regression by modeling the full conditional distribution, providing a richer understanding of the data than just the conditional mean in regression. This makes CDE particularly useful in critical appli
Externí odkaz:
http://arxiv.org/abs/2410.11449