activity
20182022
most citedHOP: History-and-Order Aware Pre-training for Vision-and-Language Navigation

8 citations · 10 across the 6 of their papers we have counts for

collaborators

7 papers

cond-mat.supr-con2021

Observation of nearly identical superconducting transition temperatures in pressurized Weyl semimetal MIrTe4 (M=Nb and Ta)

Sijin Long, Shu Cai, Rico Schonemann +13

Here we report the observation of pressure-induced superconductivity in type-II Weyl semimetal (WSM) candidate NbIrTe4 and the evolution of its Hall coefficient (RH), magnetoresist…

cs.CV2021

Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention

Wei Suo, Mengyang Sun, Peng Wang +1

Referring Expression Comprehension (REC) has become one of the most important tasks in visual reasoning, since it is an essential step for many vision-and-language tasks such as vi…

cs.CV2021

Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads

Chenyu Gao, Qi Zhu, Peng Wang +1

Vision-and-Language (VL) pre-training has shown great potential on many related downstream tasks, such as Visual Question Answering (VQA), one of the most popular problems in the V…

q-fin.RM2019

Neural Learning of Online Consumer Credit Risk

Di Wang, Qi Wu, Wen Zhang

This paper takes a deep learning approach to understand consumer credit risk when e-commerce platforms issue unsecured credit to finance customers' purchase. The "NeuCredit" model…

math.OC2019

Understanding Distributional Ambiguity via Non-robust Chance Constraint

Qi Wu, Shumin Ma, Cheuk Hang Leung +2

This paper provides a non-robust interpretation of the distributionally robust optimization (DRO) problem by relating the distributional uncertainties to the chance probabilities.…

q-fin.RM2019

Cross-sectional Learning of Extremal Dependence among Financial Assets

Xing Yan, Qi Wu, Wen Zhang

We propose a novel probabilistic model to facilitate the learning of multivariate tail dependence of multiple financial assets. Our method allows one to construct from known random…