Search Results for author: Hao-Ran Wei

Found 14 papers, 3 papers with code

Learning to Navigate in Synthetically Accessible Chemical Space Using Reinforcement Learning

1 code implementation ICML 2020 Sai Krishna Gottipati, Boris Sattarov, Sufeng. Niu, Hao-Ran Wei, Yashaswi Pathak, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

In this work, we propose a novel reinforcement learning (RL) setup for drug discovery that addresses this challenge by embedding the concept of synthetic accessibility directly into the de novo compound design system.

Drug Discovery Navigate +3

Continual Learning for Neural Machine Translation

no code implementations NAACL 2021 Yue Cao, Hao-Ran Wei, Boxing Chen, Xiaojun Wan

In practical applications, NMT models are usually trained on a general domain corpus and then fine-tuned by continuing training on the in-domain corpus.

Continual Learning Knowledge Distillation +3

Incorporating BERT into Parallel Sequence Decoding with Adapters

1 code implementation NeurIPS 2020 Junliang Guo, Zhirui Zhang, Linli Xu, Hao-Ran Wei, Boxing Chen, Enhong Chen

Our framework is based on a parallel sequence decoding algorithm named Mask-Predict considering the bi-directional and conditional independent nature of BERT, and can be adapted to traditional autoregressive decoding easily.

Machine Translation Natural Language Understanding +2

Iterative Domain-Repaired Back-Translation

no code implementations EMNLP 2020 Hao-Ran Wei, Zhirui Zhang, Boxing Chen, Weihua Luo

In this paper, we focus on the domain-specific translation with low resources, where in-domain parallel corpora are scarce or nonexistent.

Domain Adaptation NMT +1

Themes Informed Audio-visual Correspondence Learning

no code implementations14 Sep 2020 Runze Su, Fei Tao, Xudong Liu, Hao-Ran Wei, Xiaorong Mei, Zhiyao Duan, Lei Yuan, Ji Liu, Yuying Xie

The applications of short-term user-generated video (UGV), such as Snapchat, and Youtube short-term videos, booms recently, raising lots of multimodal machine learning tasks.

GRET: Global Representation Enhanced Transformer

no code implementations24 Feb 2020 Rongxiang Weng, Hao-Ran Wei, Shu-Jian Huang, Heng Yu, Lidong Bing, Weihua Luo, Jia-Jun Chen

The encoder maps the words in the input sentence into a sequence of hidden states, which are then fed into the decoder to generate the output sentence.

Machine Translation Sentence +3

Objects detection for remote sensing images based on polar coordinates

no code implementations9 Jan 2020 Lin Zhou, Hao-Ran Wei, Hao Li, Wenzhe Zhao, Yi Zhang, Yue Zhang

In this article, we introduce the polar coordinate system to the deep learning detector for the first time, and propose an anchor free Polar Remote Sensing Object Detector (P-RSDet), which can achieve competitive detection accuracy via uses simpler object representation model and less regression parameters.

Object object-detection +3

Oriented Objects as pairs of Middle Lines

no code implementations23 Dec 2019 Hao-Ran Wei, Yue Zhang, Zhonghan Chang, Hao Li, Hongqi Wang, Xian Sun

It is noteworthy that the objects in COCO can be regard as a special form of oriented objects with an angle of 90 degrees.

object-detection Object Detection In Aerial Images +4

Generating Diverse Translation by Manipulating Multi-Head Attention

no code implementations21 Nov 2019 Zewei Sun, Shu-Jian Huang, Hao-Ran Wei, Xin-yu Dai, Jia-Jun Chen

Experiments also show that back-translation with these diverse translations could bring significant improvement on performance on translation tasks.

Data Augmentation Machine Translation +3

Multiple-objective Reinforcement Learning for Inverse Design and Identification

no code implementations9 Oct 2019 Hao-Ran Wei, Mariefel Olarte, Garrett B. Goh

The aim of the inverse chemical design is to develop new molecules with given optimized molecular properties or objectives.

reinforcement-learning Reinforcement Learning (RL)

X-LineNet: Detecting Aircraft in Remote Sensing Images by a pair of Intersecting Line Segments

no code implementations29 Jul 2019 Hao-Ran Wei, Yue Zhang, Bing Wang, Yang Yang, Hao Li, Hongqi Wang

Motivated by the development of deep convolution neural networks (DCNNs), tremendous progress has been gained in the field of aircraft detection.

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