Search Results for author: Qi Yan

Found 10 papers, 4 papers with code

Joint Generative Modeling of Scene Graphs and Images via Diffusion Models

no code implementations2 Jan 2024 Bicheng Xu, Qi Yan, Renjie Liao, Lele Wang, Leonid Sigal

While previous works have explored image generation conditioned on scene graphs or layouts, our task is distinctive and important as it involves generating scene graphs themselves unconditionally from noise, enabling efficient and interpretable control for image generation.

Graph Generation Image Generation +2

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation

1 code implementation4 Jul 2023 Qi Yan, Zhengyang Liang, Yang song, Renjie Liao, Lele Wang

Diffusion models based on permutation-equivariant networks can learn permutation-invariant distributions for graph data.

Denoising Graph Generation

What Constitutes Good Contrastive Learning in Time-Series Forecasting?

no code implementations21 Jun 2023 Chiyu Zhang, Qi Yan, Lili Meng, Tristan Sylvain

Despite these advances, there remains a significant gap in understanding the impact of different SSCL strategies on time series forecasting performance, as well as the specific benefits that SSCL can bring.

Contrastive Learning Representation Learning +2

Hierarchically Constrained Adaptive Ad Exposure in Feeds

no code implementations31 May 2022 Dagui Chen, Qi Yan, Chunjie Chen, Zhenzhe Zheng, Yangsu Liu, Zhenjia Ma, Chuan Yu, Jian Xu, Bo Zheng

To this end, adaptive ad exposure has become an appealing strategy to boost the overall performance of the feed.

Computational Efficiency

Social NCE: Contrastive Learning of Socially-aware Motion Representations

4 code implementations ICCV 2021 Yuejiang Liu, Qi Yan, Alexandre Alahi

Learning socially-aware motion representations is at the core of recent advances in multi-agent problems, such as human motion forecasting and robot navigation in crowds.

Autonomous Navigation Motion Forecasting +1

Measurement Scheduling for Cooperative Localization in Resource-Constrained Conditions

1 code implementation10 Dec 2019 Qi Yan, Li Jiang, Solmaz Kia

Optimal selection of which teammates a robot should take a relative measurement from such that the updated joint localization uncertainty of the team is minimized is an NP-hard problem.

Robotics

Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks

no code implementations6 Nov 2018 Qi Yan, Yajing Zheng, Shanshan Jia, Yichen Zhang, Zhaofei Yu, Feng Chen, Yonghong Tian, Tiejun Huang, Jian. K. Liu

When a deep CNN with many layers is used for the visual system, it is not easy to compare the structure components of CNNs with possible neuroscience underpinnings due to highly complex circuits from the retina to higher visual cortex.

Transfer Learning

Revealing structure components of the retina by deep learning networks

no code implementations8 Nov 2017 Qi Yan, Zhaofei Yu, Feng Chen, Jian. K. Liu

By training CNNs with white noise images to predicate neural responses, we found that convolutional filters learned in the end are resembling to biological components of the retinal circuit.

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