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of 5 979
pro vyhledávání: '"Bischof, P"'
Autor:
Uppalapati, Khartik, Dandamudi, Eeshan, Ice, S. Nick, Chandra, Gaurav, Bischof, Kirsten, Lorson, Christian L., Singh, Kamal
Traditional drug discovery is a long, expensive, and complex process. Advances in Artificial Intelligence (AI) and Machine Learning (ML) are beginning to change this narrative. Here, we provide a comprehensive overview of different AI and ML tools th
Externí odkaz:
http://arxiv.org/abs/2411.06009
For efficient and safe autonomous driving, it is essential that autonomous vehicles can predict the motion of other traffic agents. While highly accurate, current motion prediction models often impose significant challenges in terms of training resou
Externí odkaz:
http://arxiv.org/abs/2409.16154
Graph Neural Networks (GNNs) excel in handling graph-structured data but often underperform in link prediction tasks compared to classical methods, mainly due to the limitations of the commonly used Message Passing GNNs (MPNNs). Notably, their abilit
Externí odkaz:
http://arxiv.org/abs/2408.12334
Accurate 3D object detection in LiDAR point clouds is crucial for autonomous driving systems. To achieve state-of-the-art performance, the supervised training of detectors requires large amounts of human-annotated data, which is expensive to obtain a
Externí odkaz:
http://arxiv.org/abs/2408.03790
Autor:
Bischof, Sebastian
Commutator blueprints can be seen as blueprints for constructing RGD-systems over $\mathbb{F}_2$ with prescribed commutation relations. In this paper we construct several families of Weyl-invariant commutator blueprints, mostly of universal type. Tog
Externí odkaz:
http://arxiv.org/abs/2407.15506
Autor:
Bischof, Sebastian
In this paper we prove that an RGD-system over $\mathbb{F}_2$ with prescribed commutation relations exists if and only if the commutation relations are Weyl-invariant and can be realized in the group $U_+$. This result gives us a machinery to produce
Externí odkaz:
http://arxiv.org/abs/2407.15503
Autor:
Watson, Matthew, Sreepathihalli, Divyashree Shivakumar, Chollet, Francois, Gorner, Martin, Sodhia, Kiranbir, Sampath, Ramesh, Patel, Tirth, Jin, Haifeng, Kovelamudi, Neel, Rasskin, Gabriel, Saadat, Samaneh, Wood, Luke, Qian, Chen, Bischof, Jonathan, Stenbit, Ian, Sharma, Abheesht, Mishra, Anshuman
We present the Keras domain packages KerasCV and KerasNLP, extensions of the Keras API for Computer Vision and Natural Language Processing workflows, capable of running on either JAX, TensorFlow, or PyTorch. These domain packages are designed to enab
Externí odkaz:
http://arxiv.org/abs/2405.20247
Understanding human behavior fundamentally relies on accurate 3D human pose estimation. Graph Convolutional Networks (GCNs) have recently shown promising advancements, delivering state-of-the-art performance with rather lightweight architectures. In
Externí odkaz:
http://arxiv.org/abs/2405.17397
Autor:
Bischof, Sebastian
Let $(W, S)$ be a Coxeter system of rank $n$ and let $p_{(W, S)}(t)$ be its growth function. It is known that $p_{(W, S)}(q^{-1}) < \infty$ holds for all $n \leq q \in \mathbb{N}$. In this paper we will show that this still holds for $q = n-1$, if $(
Externí odkaz:
http://arxiv.org/abs/2405.10617
Publikováno v:
BMVC 2024
State-of-the-art Multiple Object Tracking (MOT) approaches have shown remarkable performance when trained and evaluated on current benchmarks. However, these benchmarks primarily consist of clear weather scenarios, overlooking adverse atmospheric con
Externí odkaz:
http://arxiv.org/abs/2404.10534