566 citations · 716 across the 21 of their papers we have counts for
8 papers · 1 filter
De Novo Molecular Generation via Connection-aware Motif Mining
Zijie Geng, Shufang Xie, Yingce Xia +6
De novo molecular generation is an essential task for science discovery. Recently, fragment-based deep generative models have attracted much research attention due to their flexibi…
Unified 2D and 3D Pre-Training of Molecular Representations
Jinhua Zhu, Yingce Xia, Lijun Wu +5
Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represent…
Dynamic Relation Discovery and Utilization in Multi-Entity Time Series Forecasting
Lin Huang, Lijun Wu, Jia Zhang +2
Time series forecasting plays a key role in a variety of domains. In a lot of real-world scenarios, there exist multiple forecasting entities (e.g. power station in the solar syste…
Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
Shiqi Gong, Qi Meng, Yue Wang +4
Learning dynamics governed by differential equations is crucial for predicting and controlling the systems in science and engineering. Neural Ordinary Differential Equation (NODE),…
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu +1
Stock trend forecasting has become a popular research direction that attracts widespread attention in the financial field. Though deep learning methods have achieved promising resu…
Learning to Reweight with Deep Interactions
Yang Fan, Yingce Xia, Lijun Wu +5
Recently, the concept of teaching has been introduced into machine learning, in which a teacher model is used to guide the training of a student model (which will be used in real t…
Learning to Teach with Dynamic Loss Functions
Lijun Wu, Fei Tian, Yingce Xia +4
Teaching is critical to human society: it is with teaching that prospective students are educated and human civilization can be inherited and advanced. A good teacher not only prov…
A Study of Reinforcement Learning for Neural Machine Translation
Lijun Wu, Fei Tian, Tao Qin +2
Recent studies have shown that reinforcement learning (RL) is an effective approach for improving the performance of neural machine translation (NMT) system. However, due to its in…