Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Pándy, Michal"'
Autor:
Pándy, Michal, Qiu, Weikang, Corso, Gabriele, Veličković, Petar, Ying, Rex, Leskovec, Jure, Liò, Pietro
Searching for a path between two nodes in a graph is one of the most well-studied and fundamental problems in computer science. In numerous domains such as robotics, AI, or biology, practitioners develop search heuristics to accelerate their pathfind
Externí odkaz:
http://arxiv.org/abs/2212.03978
Transferability metrics is a maturing field with increasing interest, which aims at providing heuristics for selecting the most suitable source models to transfer to a given target dataset, without fine-tuning them all. However, existing works rely o
Externí odkaz:
http://arxiv.org/abs/2204.01403
Transfer learning has become a popular method for leveraging pre-trained models in computer vision. However, without performing computationally expensive fine-tuning, it is difficult to quantify which pre-trained source models are suitable for a spec
Externí odkaz:
http://arxiv.org/abs/2111.12780
The development of data-dependent heuristics and representations for biological sequences that reflect their evolutionary distance is critical for large-scale biological research. However, popular machine learning approaches, based on continuous Eucl
Externí odkaz:
http://arxiv.org/abs/2109.09740
We demonstrate that challenging shortest path problems can be solved via direct spline regression from a neural network, trained in an unsupervised manner (i.e. without requiring ground truth optimal paths for training). To achieve this, we derive a
Externí odkaz:
http://arxiv.org/abs/2011.14787