Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Bekas, Costas"'
Autor:
Schwaller, Philippe, Petraglia, Riccardo, Zullo, Valerio, Nair, Vishnu H, Haeuselmann, Rico Andreas, Pisoni, Riccardo, Bekas, Costas, Iuliano, Anna, Laino, Teodoro
We present an extension of our Molecular Transformer architecture combined with a hyper-graph exploration strategy for automatic retrosynthesis route planning without human intervention. The single-step retrosynthetic model sets a new state of the ar
Externí odkaz:
http://arxiv.org/abs/1910.08036
Deep neural networks achieve outstanding results in challenging image classification tasks. However, the design of network topologies is a complex task and the research community makes a constant effort in discovering top-accuracy topologies, either
Externí odkaz:
http://arxiv.org/abs/1909.10818
Autor:
Mariani, Giovanni, Zhu, Yada, Li, Jianbo, Scheidegger, Florian, Istrate, Roxana, Bekas, Costas, Malossi, A. Cristiano I.
Since decades, the data science community tries to propose prediction models of financial time series. Yet, driven by the rapid development of information technology and machine intelligence, the velocity of today's information leads to high market e
Externí odkaz:
http://arxiv.org/abs/1909.10578
Autor:
Manica, Matteo, Auer, Christoph, Weber, Valery, Zipoli, Federico, Dolfi, Michele, Staar, Peter, Laino, Teodoro, Bekas, Costas, Fujita, Akihiro, Toda, Hiroki, Hirose, Shuichi, Orii, Yasumitsu
Information extraction and data mining in biochemical literature is a daunting task that demands resource-intensive computation and appropriate means to scale knowledge ingestion. Being able to leverage this immense source of technical information he
Externí odkaz:
http://arxiv.org/abs/1907.08400
Autor:
Sood, Atin, Elder, Benjamin, Herta, Benjamin, Xue, Chao, Bekas, Costas, Malossi, A. Cristiano I., Saha, Debashish, Scheidegger, Florian, Venkataraman, Ganesh, Thomas, Gegi, Mariani, Giovanni, Strobelt, Hendrik, Samulowitz, Horst, Wistuba, Martin, Manica, Matteo, Choudhury, Mihir, Yan, Rong, Istrate, Roxana, Puri, Ruchir, Pedapati, Tejaswini
Application of neural networks to a vast variety of practical applications is transforming the way AI is applied in practice. Pre-trained neural network models available through APIs or capability to custom train pre-built neural network architecture
Externí odkaz:
http://arxiv.org/abs/1901.06261
Autor:
Schwaller, Philippe, Laino, Teodoro, Gaudin, Théophile, Bolgar, Peter, Bekas, Costas, Lee, Alpha A
Publikováno v:
ACS Central Science, 2019
Organic synthesis is one of the key stumbling blocks in medicinal chemistry. A necessary yet unsolved step in planning synthesis is solving the forward problem: given reactants and reagents, predict the products. Similar to other work, we treat react
Externí odkaz:
http://arxiv.org/abs/1811.02633
Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can ingest these documents at scale and make the contained knowledge disco
Externí odkaz:
http://arxiv.org/abs/1806.02284
Over the past few decades, the amount of scientific articles and technical literature has increased exponentially in size. Consequently, there is a great need for systems that can ingest these documents at scale and make their content discoverable. U
Externí odkaz:
http://arxiv.org/abs/1805.09687
We propose an incremental training method that partitions the original network into sub-networks, which are then gradually incorporated in the running network during the training process. To allow for a smooth dynamic growth of the network, we introd
Externí odkaz:
http://arxiv.org/abs/1803.10232
Autor:
Scheidegger, Florian, Istrate, Roxana, Mariani, Giovanni, Benini, Luca, Bekas, Costas, Malossi, Cristiano
In the deep-learning community new algorithms are published at an incredible pace. Therefore, solving an image classification problem for new datasets becomes a challenging task, as it requires to re-evaluate published algorithms and their different
Externí odkaz:
http://arxiv.org/abs/1803.09588