no code implementations • NeurIPS 2019 • Florian Scheidegger, Luca Benini, Costas Bekas, A. Cristiano I. Malossi
The narrow-space search of floating-point models improves the accuracy on CIFAR10 of an established IoT model from 70. 64% to 74. 87% within the same memory constraints.
no code implementations • 17 Oct 2019 • Philippe Schwaller, Riccardo Petraglia, Valerio Zullo, Vishnu H Nair, Rico Andreas Haeuselmann, Riccardo Pisoni, Costas Bekas, Anna Iuliano, Teodoro Laino
We present an extension of our Molecular Transformer architecture combined with a hyper-graph exploration strategy for automatic retrosynthesis route planning without human intervention.
no code implementations • 24 Sep 2019 • Florian Scheidegger, Luca Benini, Costas Bekas, Cristiano Malossi
We further improve the accuracy to 82. 07% by including 16-bit half types and we obtain the best accuracy of 83. 45% by extending the search with model optimized IEEE 754 reduced types.
no code implementations • 19 Sep 2019 • Giovanni Mariani, Yada Zhu, Jianbo Li, Florian Scheidegger, Roxana Istrate, Costas Bekas, A. Cristiano I. Malossi
Sound financial theories demonstrate that in an efficient marketplace all information available today, including expectations on future events, are represented in today prices whereas future price trend is driven by the uncertainty.
Computational Finance Statistical Finance
no code implementations • 19 Jul 2019 • Matteo Manica, Christoph Auer, Valery Weber, Federico Zipoli, Michele Dolfi, Peter Staar, Teodoro Laino, Costas Bekas, Akihiro Fujita, Hiroki Toda, Shuichi Hirose, Yasumitsu Orii
Information extraction and data mining in biochemical literature is a daunting task that demands resource-intensive computation and appropriate means to scale knowledge ingestion.
no code implementations • 17 Jan 2019 • Atin Sood, Benjamin Elder, Benjamin Herta, Chao Xue, Costas Bekas, A. Cristiano I. Malossi, Debashish Saha, Florian Scheidegger, Ganesh Venkataraman, Gegi Thomas, Giovanni Mariani, Hendrik Strobelt, Horst Samulowitz, Martin Wistuba, Matteo Manica, Mihir Choudhury, Rong Yan, Roxana Istrate, Ruchir Puri, Tejaswini Pedapati
Application of neural networks to a vast variety of practical applications is transforming the way AI is applied in practice.
1 code implementation • 6 Nov 2018 • Philippe Schwaller, Teodoro Laino, Théophile Gaudin, Peter Bolgar, Costas Bekas, Alpha A. Lee
Organic synthesis is one of the key stumbling blocks in medicinal chemistry.
no code implementations • 24 May 2018 • Peter W J Staar, Michele Dolfi, Christoph Auer, Costas Bekas
In this paper, we present a modular, cloud-based platform to ingest documents at scale.
no code implementations • 15 May 2018 • Peter W J Staar, Michele Dolfi, Christoph Auer, Costas Bekas
We present a platform to ingest documents at scale which is powered by Machine Learning techniques and allows the user to train custom models on document collections.
no code implementations • 27 Mar 2018 • Roxana Istrate, Adelmo Cristiano Innocenza Malossi, Costas Bekas, Dimitrios Nikolopoulos
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.
1 code implementation • 26 Mar 2018 • Florian Scheidegger, Roxana Istrate, Giovanni Mariani, Luca Benini, Costas Bekas, Cristiano Malossi
In the deep-learning community new algorithms are published at an incredible pace.
4 code implementations • 26 Mar 2018 • Giovanni Mariani, Florian Scheidegger, Roxana Istrate, Costas Bekas, Cristiano Malossi
The generator in the GAN is initialized with the encoder module of an autoencoder that enables us to learn an accurate class-conditioning in the latent space.
1 code implementation • 13 Nov 2017 • Philippe Schwaller, Theophile Gaudin, David Lanyi, Costas Bekas, Teodoro Laino
With this approach, we demonstrate results superior to the state-of-the-art solution by a significant margin on the top-1 accuracy.
no code implementations • 16 Jan 2017 • Manuel Le Gallo, Abu Sebastian, Roland Mathis, Matteo Manica, Heiner Giefers, Tomas Tuma, Costas Bekas, Alessandro Curioni, Evangelos Eleftheriou
As CMOS scaling reaches its technological limits, a radical departure from traditional von Neumann systems, which involve separate processing and memory units, is needed in order to significantly extend the performance of today's computers.
Emerging Technologies