Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Santos, Cicero dos"'
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics
Autor:
Das, Payel, Sercu, Tom, Wadhawan, Kahini, Padhi, Inkit, Gehrmann, Sebastian, Cipcigan, Flaviu, Chenthamarakshan, Vijil, Strobelt, Hendrik, Santos, Cicero dos, Chen, Pin-Yu, Yang, Yi Yan, Tan, Jeremy, Hedrick, James, Crain, Jason, Mojsilovic, Aleksandra
Publikováno v:
Nature Biomedical Engineering (2021)
De novo therapeutic design is challenged by a vast chemical repertoire and multiple constraints, e.g., high broad-spectrum potency and low toxicity. We propose CLaSS (Controlled Latent attribute Space Sampling) - an efficient computational method for
Externí odkaz:
http://arxiv.org/abs/2005.11248
We propose the Sobolev Independence Criterion (SIC), an interpretable dependency measure between a high dimensional random variable X and a response variable Y . SIC decomposes to the sum of feature importance scores and hence can be used for nonline
Externí odkaz:
http://arxiv.org/abs/1910.14212
In this paper we propose to perform model ensembling in a multiclass or a multilabel learning setting using Wasserstein (W.) barycenters. Optimal transport metrics, such as the Wasserstein distance, allow incorporating semantic side information such
Externí odkaz:
http://arxiv.org/abs/1902.04999
Autor:
Das, Payel, Wadhawan, Kahini, Chang, Oscar, Sercu, Tom, Santos, Cicero Dos, Riemer, Matthew, Chenthamarakshan, Vijil, Padhi, Inkit, Mojsilovic, Aleksandra
Given the emerging global threat of antimicrobial resistance, new methods for next-generation antimicrobial design are urgently needed. We report a peptide generation framework PepCVAE, based on a semi-supervised variational autoencoder (VAE) model,
Externí odkaz:
http://arxiv.org/abs/1810.07743
Relation detection is a core component for many NLP applications including Knowledge Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural network enhanced by residual learning that detects KB relations given an in
Externí odkaz:
http://arxiv.org/abs/1704.06194
In this work, we propose a deep learning approach to improve docking-based virtual screening. The introduced deep neural network, DeepVS, uses the output of a docking program and learns how to extract relevant features from basic data such as atom an
Externí odkaz:
http://arxiv.org/abs/1608.04844
In this work, we propose Attentive Pooling (AP), a two-way attention mechanism for discriminative model training. In the context of pair-wise ranking or classification with neural networks, AP enables the pooling layer to be aware of the current inpu
Externí odkaz:
http://arxiv.org/abs/1602.03609
In this paper, we apply a general deep learning (DL) framework for the answer selection task, which does not depend on manually defined features or linguistic tools. The basic framework is to build the embeddings of questions and answers based on bid
Externí odkaz:
http://arxiv.org/abs/1511.04108
Autor:
Santos, Cícero dos
Publikováno v:
Biblioteca Digital de Teses e Dissertações da UEPBUniversidade Estadual da ParaíbaUEPB.
Submitted by Jean Medeiros (jeanletras@uepb.edu.br) on 2016-03-23T13:46:36Z No. of bitstreams: 1 PDF - Cícero dos Santos.pdf: 10392440 bytes, checksum: 7d26458c22e6a36db9fd4f916e5b62c8 (MD5)
Approved for entry into archive by Secta BC (secta.cs
Approved for entry into archive by Secta BC (secta.cs
Externí odkaz:
http://tede.bc.uepb.edu.br/tede/jspui/handle/tede/2384
