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20212023
most citedCausality Inspired Representation Learning for Domain Generalization

13 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

hep-ph2023

Resonances from a Neural Network-based Partial Wave Analysis on Scattering

Jun Shi, Long-Cheng Gui, Jian Liang +1

We implement a convolutional neural network to study the hyperons using experimental data of the reaction. The averaged accuracy of the NN models in resolving res…

cs.IR2022

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction

Xiaochen Li, Rui Zhong, Jian Liang +2

Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction. To improve the richness, collecting long…

cs.LG2022★ 13 cited

Causality Inspired Representation Learning for Domain Generalization

Fangrui Lv, Jian Liang, Shuang Li +4

Domain generalization (DG) is essentially an out-of-distribution problem, aiming to generalize the knowledge learned from multiple source domains to an unseen target domain. The ma…

cs.LG2021★ 8 cited

Pareto Domain Adaptation

Fangrui Lv, Jian Liang, Kaixiong Gong +5

Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source. To achieve…

cs.CV2021★ 7 cited

NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion

Chenfei Wu, Jian Liang, Lei Ji +4

This paper presents a unified multimodal pre-trained model called NÜWA that can generate new or manipulate existing visual data (i.e., images and videos) for various visual synthes…