Search Results for author: Yuncong Chen

Found 12 papers, 4 papers with code

Interpretable Imitation Learning with Dynamic Causal Relations

no code implementations30 Sep 2023 Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen

After the model is learned, we can obtain causal relations among states and action variables behind its decisions, exposing policies learned by it.

Causal Discovery Imitation Learning

GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection

1 code implementation12 Sep 2023 Yufei Li, Yanchi Liu, Haoyu Wang, Zhengzhang Chen, Wei Cheng, Yuncong Chen, Wenchao Yu, Haifeng Chen, Cong Liu

Subsequently, GLAD utilizes a temporal-attentive graph edge anomaly detection model for identifying anomalous relations in these dynamic log graphs.

Anomaly Detection Few-Shot Learning

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations

1 code implementation13 Jun 2023 Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen

Imitation learning has achieved great success in many sequential decision-making tasks, in which a neural agent is learned by imitating collected human demonstrations.

Disentanglement Imitation Learning

Time Series Contrastive Learning with Information-Aware Augmentations

1 code implementation21 Mar 2023 Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang

A key component of contrastive learning is to select appropriate augmentations imposing some priors to construct feasible positive samples, such that an encoder can be trained to learn robust and discriminative representations.

Contrastive Learning Open-Ended Question Answering +2

Deep Federated Anomaly Detection for Multivariate Time Series Data

no code implementations9 May 2022 Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng, Bo Zong, Takehiko Mizoguchi, Cristian Lumezanu, Haifeng Chen, Jiebo Luo

Specifically, we first design an Exemplar-based Deep Neural network (ExDNN) to learn local time series representations based on their compatibility with an exemplar module which consists of hidden parameters learned to capture varieties of normal patterns on each edge device.

Constrained Clustering Federated Learning +3

SEED: Sound Event Early Detection via Evidential Uncertainty

no code implementations5 Feb 2022 Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen

Sound Event Early Detection (SEED) is an essential task in recognizing the acoustic environments and soundscapes.

Event Detection Sound Event Detection

Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series

no code implementations24 Jan 2022 Jurijs Nazarovs, Cristian Lumezanu, Qianying Ren, Yuncong Chen, Takehiko Mizoguchi, Dongjin Song, Haifeng Chen

In this paper, we propose an ordered time series classification framework that is robust against missing classes in the training data, i. e., during testing we can prescribe classes that are missing during training.

Missing Labels Retrieval +3

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection

no code implementations29 Jul 2021 Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen

Next, a dual discriminator based adversarial training procedure, which jointly considers an image discriminator that can maintain the local consistency at frame-level and a video discriminator that can enforce the global coherence of temporal dynamics, is employed to enhance the future frame prediction.

Anomaly Detection Video Anomaly Detection

3D Fusion of Infrared Images with Dense RGB Reconstruction from Multiple Views -- with Application to Fire-fighting Robots

no code implementations29 Jul 2020 Yuncong Chen, Will Warren

This project integrates infrared and RGB imagery to produce dense 3D environment models reconstructed from multiple views.

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

5 code implementations20 Nov 2018 Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla

Subsequently, given the signature matrices, a convolutional encoder is employed to encode the inter-sensor (time series) correlations and an attention based Convolutional Long-Short Term Memory (ConvLSTM) network is developed to capture the temporal patterns.

Time Series Time Series Anomaly Detection +1

Robust Landmark Detection for Alignment of Mouse Brain Section Images

no code implementations9 Mar 2018 Yuncong Chen, David Kleinfeld, Martyn Goulding, Yoav Freund

In this work we describe the first steps in developing a semi-automated system to construct a histology at- las of mouse brainstem that combines atlas-guided annotation, landmark-based registration and atlas generation in an iterative framework.

The Active Atlas: Combining 3D Anatomical Models with Texture Detectors

no code implementations28 Feb 2017 Yuncong Chen, Lauren McElvain, Alex Tolpygo, Daniel Ferrante, Harvey Karten, Partha Mitra, David Kleinfeld, Yoav Freund

We have developed a digital atlas methodology that combines information about the 3D organization of the brain and the detailed texture of neurons in different structures.

Anatomy

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