Search Results for author: Sen Song

Found 21 papers, 6 papers with code

Contrastive Learning of Shared Spatiotemporal EEG Representations Across Individuals for Naturalistic Neuroscience

no code implementations22 Feb 2024 Xinke Shen, Lingyi Tao, Xuyang Chen, Sen Song, Quanying Liu, Dan Zhang

Targeting the Electroencephalogram (EEG) technique, known for its rich spatial and temporal information, this study presents a general framework for Contrastive Learning of Shared SpatioTemporal EEG Representations across individuals (CL-SSTER).

Brain Decoding Contrastive Learning +2

UniMem: Towards a Unified View of Long-Context Large Language Models

no code implementations5 Feb 2024 Junjie Fang, Likai Tang, Hongzhe Bi, Yujia Qin, Si Sun, Zhenyu Li, Haolun Li, Yongjian Li, Xin Cong, Yukun Yan, Xiaodong Shi, Sen Song, Yankai Lin, Zhiyuan Liu, Maosong Sun

Although there exist various methods devoted to enhancing the long-context processing ability of large language models (LLMs), they are developed in an isolated manner and lack systematic analysis and integration of their strengths, hindering further developments.

Management

Brain-Like Replay Naturally Emerges in Reinforcement Learning Agents

no code implementations2 Feb 2024 Jiyi Wang, Likai Tang, Huimiao Chen, Sen Song

Can replay, as a widely observed neural activity pattern in brain regions, particularly in the hippocampus and neocortex, emerge in an artificial agent?

Hippocampus reinforcement-learning

OpenChat: Advancing Open-source Language Models with Mixed-Quality Data

1 code implementation20 Sep 2023 Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, Yang Liu

Specifically, we consider the general SFT training data, consisting of a small amount of expert data mixed with a large proportion of sub-optimal data, without any preference labels.

Arithmetic Reasoning Code Generation +1

AI of Brain and Cognitive Sciences: From the Perspective of First Principles

no code implementations20 Jan 2023 Luyao Chen, Zhiqiang Chen, Longsheng Jiang, Xiang Liu, Linlu Xu, Bo Zhang, Xiaolong Zou, Jinying Gao, Yu Zhu, Xizi Gong, Shan Yu, Sen Song, Liangyi Chen, Fang Fang, Si Wu, Jia Liu

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation.

Few-Shot Learning Image Classification

Simulated annealing for optimization of graphs and sequences

no code implementations1 Oct 2021 Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, Huasong Zhong, Jie zhou, Lili Mou, Sen Song

The key idea is to integrate powerful neural networks into metaheuristics (e. g., simulated annealing, SA) to restrict the search space in discrete optimization.

Paraphrase Generation

Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition

no code implementations20 Sep 2021 Xinke Shen, Xianggen Liu, Xin Hu, Dan Zhang, Sen Song

Contrastive learning was employed to minimize the inter-subject differences by maximizing the similarity in EEG signal representations across subjects when they received the same emotional stimuli in contrast to different ones.

Contrastive Learning EEG +5

An effective self-supervised framework for learning expressive molecular global representations to drug discovery

1 code implementation Briefings in Bioinformatics 2021 Pengyong Li, Jun Wang, Yixuan Qiao, Hao Chen, Yihuan Yu, Xiaojun Yao, Peng Gao, Guotong Xie, Sen Song

In MPG, we proposed a powerful GNN for modelling molecular graph named MolGNet, and designed an effective self-supervised strategy for pre-training the model at both the node and graph-level.

Drug Discovery

Learn molecular representations from large-scale unlabeled molecules for drug discovery

no code implementations21 Dec 2020 Pengyong Li, Jun Wang, Yixuan Qiao, Hao Chen, Yihuan Yu, Xiaojun Yao, Peng Gao, Guotong Xie, Sen Song

Here, we proposed a novel Molecular Pre-training Graph-based deep learning framework, named MPG, that leans molecular representations from large-scale unlabeled molecules.

Drug Discovery

TrimNet: learning molecular representation from triplet messages for biomedicine

1 code implementation4 Nov 2020 Pengyong Li, Yuquan Li, Chang-Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song, Xiaojun Yao

These advantages have established TrimNet as a powerful and useful computational tool in solving the challenging problem of molecular representation learning.

Drug Discovery Molecular Property Prediction +3

Pre-training of Graph Neural Network for Modeling Effects of Mutations on Protein-Protein Binding Affinity

no code implementations28 Aug 2020 Xianggen Liu, Yunan Luo, Sen Song, Jian Peng

Modeling the effects of mutations on the binding affinity plays a crucial role in protein engineering and drug design.

Protein Design

Brain-inspired global-local learning incorporated with neuromorphic computing

no code implementations5 Jun 2020 Yujie Wu, Rong Zhao, Jun Zhu, Feng Chen, Mingkun Xu, Guoqi Li, Sen Song, Lei Deng, Guanrui Wang, Hao Zheng, Jing Pei, Youhui Zhang, Mingguo Zhao, Luping Shi

We demonstrate the advantages of this model in multiple different tasks, including few-shot learning, continual learning, and fault-tolerance learning in neuromorphic vision sensors.

Continual Learning Few-Shot Learning

Zooming Network

no code implementations4 Oct 2018 Yukun Yan, Daqi Zheng, Zhengdong Lu, Sen Song

Structural information is important in natural language understanding.

Natural Language Understanding

JUMPER: Learning When to Make Classification Decisions in Reading

no code implementations6 Jul 2018 Xianggen Liu, Lili Mou, Haotian Cui, Zhengdong Lu, Sen Song

Both the classification result and when to make the classification are part of the decision process, which is controlled by a policy network and trained with reinforcement learning.

General Classification text-classification +1

Estimation of the volume of the left ventricle from MRI images using deep neural networks

1 code implementation13 Feb 2017 Fangzhou Liao, Xi Chen, Xiaolin Hu, Sen Song

In 2016, Kaggle organized a competition to estimate the volume of LV from MRI images.

CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling

no code implementations1 Jun 2016 Zhaofei Yu, David Kappel, Robert Legenstein, Sen Song, Feng Chen, Wolfgang Maass

Our theoretical analysis shows that stochastic search could in principle even attain optimal network configurations by emulating one of the most well-known nonlinear optimization methods, simulated annealing.

Attentional Neural Network: Feature Selection Using Cognitive Feedback

1 code implementation NeurIPS 2014 Qian Wang, Jiaxing Zhang, Sen Song, Zheng Zhang

Attentional Neural Network is a new framework that integrates top-down cognitive bias and bottom-up feature extraction in one coherent architecture.

feature selection General Classification

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