Search Results for author: Ruichen Li

Found 13 papers, 6 papers with code

DOF: Accelerating High-order Differential Operators with Forward Propagation

no code implementations15 Feb 2024 Ruichen Li, Chuwei Wang, Haotian Ye, Di He, LiWei Wang

Solving partial differential equations (PDEs) efficiently is essential for analyzing complex physical systems.

Dataset for predicting cybersickness from a virtual navigation task

no code implementations7 Feb 2023 Yuyang Wang, Ruichen Li, Jean-Rémy Chardonnet, Pan Hui

This work presents a dataset collected to predict cybersickness in virtual reality environments.

Reconstruction Task Finds Universal Winning Tickets

no code implementations23 Feb 2022 Ruichen Li, Binghui Li, Qi Qian, LiWei Wang

Pruning well-trained neural networks is effective to achieve a promising accuracy-efficiency trade-off in computer vision regimes.

Image Reconstruction object-detection +1

MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition

no code implementations27 Oct 2021 Jinming Zhao, Ruichen Li, Qin Jin, Xinchao Wang, Haizhou Li

Multimodal emotion recognition study is hindered by the lack of labelled corpora in terms of scale and diversity, due to the high annotation cost and label ambiguity.

Emotion Classification Multimodal Emotion Recognition +1

Missing Modality Imagination Network for Emotion Recognition with Uncertain Missing Modalities

1 code implementation ACL 2021 Jinming Zhao, Ruichen Li, Qin Jin

However, in real-world applications, we often encounter the problem of missing modality, and which modalities will be missing is uncertain.

Emotion Recognition

Towards a Theoretical Framework of Out-of-Distribution Generalization

no code implementations NeurIPS 2021 Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, LiWei Wang

We also introduce a new concept of expansion function, which characterizes to what extent the variance is amplified in the test domains over the training domains, and therefore give a quantitative meaning of invariant features.

Domain Generalization Model Selection +1

ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning

1 code implementation15 Feb 2021 Naichen Shi, Ruichen Li, Sun Youran

Since trick-taking game requires high level of not only reasoning, but also inference to excel, it can be a new milestone for imperfect information game AI.

Bayesian Inference reinforcement-learning +1

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