Search Results for author: Sirui Xie

Found 13 papers, 6 papers with code

Latent Diffusion Energy-Based Model for Interpretable Text Modeling

1 code implementation13 Jun 2022 Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu

Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling.

Emergent Graphical Conventions in a Visual Communication Game

no code implementations28 Nov 2021 Shuwen Qiu, Sirui Xie, Lifeng Fan, Tao Gao, Song-Chun Zhu, Yixin Zhu

While recent studies of emergent communication primarily focus on symbolic languages, their settings overlook the graphical sketches existing in human communication; they do not account for the evolution process through which symbolic sign systems emerge in the trade-off between iconicity and symbolicity.

Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning

no code implementations25 Nov 2021 Chi Zhang, Sirui Xie, Baoxiong Jia, Ying Nian Wu, Song-Chun Zhu, Yixin Zhu

Extensive experiments show that by incorporating an algebraic treatment, the ALANS learner outperforms various pure connectionist models in domains requiring systematic generalization.

Systematic Generalization

Unsupervised Foreground Extraction via Deep Region Competition

1 code implementation NeurIPS 2021 Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

Foreground extraction can be viewed as a special case of generic image segmentation that focuses on identifying and disentangling objects from the background.

Inductive Bias Semantic Segmentation

HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving

no code implementations22 Feb 2021 Sirui Xie, Xiaojian Ma, Peiyu Yu, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

Leveraging these concepts, they could understand the internal structure of this task, without seeing all of the problem instances.

Learning Algebraic Representation for Abstract Spatial-Temporal Reasoning

no code implementations1 Jan 2021 Chi Zhang, Sirui Xie, Baoxiong Jia, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

We further show that the algebraic representation learned can be decoded by isomorphism and used to generate an answer.

Systematic Generalization

Generalized Inverse Planning: Learning Lifted non-Markovian Utility for Generalizable Task Representation

no code implementations12 Nov 2020 Sirui Xie, Feng Gao, Song-Chun Zhu

Seeing that the proposed generalization problem has not been widely studied yet, we carefully define an evaluation protocol, with which we illustrate the effectiveness of MEIP on two proof-of-concept domains and one challenging task: learning to fold from demonstrations.

Understanding the wiring evolution in differentiable neural architecture search

1 code implementation2 Sep 2020 Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin

To this end, we pose questions that future differentiable methods for neural wiring discovery need to confront, hoping to evoke a discussion and rethinking on how much bias has been enforced implicitly in existing NAS methods.

Neural Architecture Search

DSNAS: Direct Neural Architecture Search without Parameter Retraining

1 code implementation CVPR 2020 Shoukang Hu, Sirui Xie, Hehui Zheng, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin

We argue that given a computer vision task for which a NAS method is expected, this definition can reduce the vaguely-defined NAS evaluation to i) accuracy of this task and ii) the total computation consumed to finally obtain a model with satisfying accuracy.

Neural Architecture Search

Learning a Decision Module by Imitating Driver's Control Behaviors

no code implementations30 Nov 2019 Junning Huang, Sirui Xie, Jiankai Sun, Qiurui Ma, Chunxiao Liu, Jianping Shi, Dahua Lin, Bolei Zhou

In this work, we propose a hybrid framework to learn neural decisions in the classical modular pipeline through end-to-end imitation learning.

Autonomous Driving Imitation Learning

Graph-guided Architecture Search for Real-time Semantic Segmentation

1 code implementation CVPR 2020 Peiwen Lin, Peng Sun, Guangliang Cheng, Sirui Xie, Xi Li, Jianping Shi

Unlike previous works that use a simplified search space and stack a repeatable cell to form a network, we introduce a novel search mechanism with new search space where a lightweight model can be effectively explored through the cell-level diversity and latencyoriented constraint.

Real-Time Semantic Segmentation

SNAS: Stochastic Neural Architecture Search

2 code implementations ICLR 2019 Sirui Xie, Hehui Zheng, Chunxiao Liu, Liang Lin

In experiments on CIFAR-10, SNAS takes less epochs to find a cell architecture with state-of-the-art accuracy than non-differentiable evolution-based and reinforcement-learning-based NAS, which is also transferable to ImageNet.

Neural Architecture Search reinforcement-learning

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