Ruixiang Zhang | DeepAI

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∙ 10/19/2022

HAVANA: Hard negAtiVe sAmples aware self-supervised coNtrastive leArning for Airborne laser scanning point clouds semantic segmentation

Deep Neural Network (DNN) based point cloud semantic segmentation has pr...

1 Yunsheng Zhang, et al. ∙

∙ 10/11/2022

Robust and Controllable Object-Centric Learning through Energy-based Models

Humans are remarkably good at understanding and reasoning about complex ...

12 Ruixiang Zhang, et al. ∙

∙ 08/08/2022

Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning

We present Bit Diffusion: a simple and generic approach for generating d...

4 Ting Chen, et al. ∙

∙ 02/27/2022

Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregation

LiDAR sensor is essential to the perception system in autonomous vehicle...

5 Song Wang, et al. ∙

∙ 02/04/2022

Learning Representation from Neural Fisher Kernel with Low-rank Approximation

In this paper, we study the representation of neural networks from the v...

17 Ruixiang Zhang, et al. ∙

∙ 11/29/2021

Rank-Constrained Least-Squares: Prediction and Inference

In this work, we focus on the high-dimensional trace regression model wi...

0 Michael Law, et al. ∙

∙ 05/28/2021

An Attention Free Transformer

We introduce Attention Free Transformer (AFT), an efficient variant of T...

37 Shuangfei Zhai, et al. ∙

∙ 03/24/2021

RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation

Point clouds can be represented in many forms (views), typically, point-...

3 Jianyun Xu, et al. ∙

∙ 12/21/2020

Improving unsupervised anomaly localization by applying multi-scale memories to autoencoders

Autoencoder and its variants have been widely applicated in anomaly dete...

8 Yifei Yang, et al. ∙

∙ 07/21/2020

Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective

Learning controllable and generalizable representation of multivariate d...

0 Ruixiang Zhang, et al. ∙

∙ 03/12/2020

Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling

We show that the sum of the implicit generator log-density log p_g of a ...

24 Tong Che, et al. ∙

∙ 11/18/2019

Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models

AI Safety is a major concern in many deep learning applications such as ...

26 Tong Che, et al. ∙

∙ 06/25/2019

Perceptual Generative Autoencoders

Modern generative models are usually designed to match target distributi...

5 Zijun Zhang, et al. ∙

∙ 10/30/2017

Understanding Hidden Memories of Recurrent Neural Networks

Recurrent neural networks (RNNs) have been successfully applied to vario...

0 Yao Ming, et al. ∙

∙ 02/26/2017

Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

Despite the successes in capturing continuous distributions, the applica...

0 Tong Che, et al. ∙

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