Matteo Manica | DeepAI

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Han Wang
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Ole Winther
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Sheng Shen
33 publications
Chloé Clavel
29 publications
Vijil Chenthamarakshan
27 publications
Hendrik Strobelt
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Pierre Colombo
26 publications
Stella Biderman
26 publications

∙ 01/29/2023

Unifying Molecular and Textual Representations via Multi-task Language Modelling

The recent advances in neural language models have also been successfull...

26 Dimitrios Christofidellis, et al. ∙

∙ 01/20/2023

Domain-agnostic and Multi-level Evaluation of Generative Models

While the capabilities of generative models heavily improved in differen...

7 Girmaw Abebe Tadesse, et al. ∙

∙ 08/15/2022

Z-BERT-A: a zero-shot Pipeline for Unknown Intent detection

Intent discovery is a fundamental task in NLP, and it is increasingly re...

27 Daniele Comi, et al. ∙

∙ 07/08/2022

GT4SD: Generative Toolkit for Scientific Discovery

With the growing availability of data within various scientific domains,...

25 Matteo Manica, et al. ∙

∙ 02/01/2022

Regression Transformer: Concurrent Conditional Generation and Regression by Blending Numerical and Textual Tokens

We report the Regression Transformer (RT), a method that abstracts regre...

19 Jannis Born, et al. ∙

∙ 10/15/2021

Multitask Prompted Training Enables Zero-Shot Task Generalization

Large language models have recently been shown to attain reasonable zero...

10 Victor Sanh, et al. ∙

∙ 12/18/2020

Understood in Translation, Transformers for Domain Understanding

Knowledge acquisition is the essential first step of any Knowledge Graph...

0 Dimitrios Christofidellis, et al. ∙

∙ 12/05/2020

Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks

Less than 1 annotated. Natural Language Processing (NLP) community has r...

20 Modestas Filipavicius, et al. ∙

∙ 09/23/2020

Hierarchical Pre-training for Sequence Labelling in Spoken Dialog

Sequence labelling tasks like Dialog Act and Emotion/Sentiment identific...

10 Emile Chapuis, et al. ∙

∙ 05/27/2020

PaccMann^RL on SARS-CoV-2: Designing antiviral candidates with conditional generative models

With the fast development of COVID-19 into a global pandemic, scientists...

48 Jannis Born, et al. ∙

∙ 05/27/2020

Targeted design of antiviral compounds against SARS-CoV-2 with conditional generative models

With the fast development of COVID-19 into a global pandemic, scientists...

25 Jannis Born, et al. ∙

∙ 02/21/2020

Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue

The task of predicting dialog acts (DA) based on conversational dialog i...

0 Pierre Colombo, et al. ∙

∙ 02/20/2020

Guiding attention in Sequence-to-sequence models for Dialogue Act prediction

The task of predicting dialog acts (DA) based on conversational dialog i...

0 Pierre Colombo, et al. ∙

∙ 07/19/2019

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

Information extraction and data mining in biochemical literature is a da...

0 Matteo Manica, et al. ∙

∙ 04/25/2019

Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders

In line with recent advances in neural drug design and sensitivity predi...

0 Matteo Manica, et al. ∙

∙ 01/17/2019

NeuNetS: An Automated Synthesis Engine for Neural Network Design

Application of neural networks to a vast variety of practical applicatio...

0 Atin Sood, et al. ∙

∙ 11/16/2018

PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks

We present a novel approach for the prediction of anticancer compound se...

0 Ali Oskooei, et al. ∙

∙ 08/18/2018

Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer

We present the Network-based Biased Tree Ensembles (NetBiTE) method for ...

0 Ali Oskooei, et al. ∙

∙ 03/29/2018

PIMKL: Pathway Induced Multiple Kernel Learning

Reliable identification of molecular biomarkers is essential for accurat...

0 Matteo Manica, et al. ∙

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