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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...
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10/11/2022
Robust and Controllable Object-Centric Learning through Energy-based Models
Humans are remarkably good at understanding and reasoning about complex ...
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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...
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02/27/2022
Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregation
LiDAR sensor is essential to the perception system in autonomous vehicle...
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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...
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11/29/2021
Rank-Constrained Least-Squares: Prediction and Inference
In this work, we focus on the high-dimensional trace regression model wi...
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05/28/2021
An Attention Free Transformer
We introduce Attention Free Transformer (AFT), an efficient variant of T...
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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-...
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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...
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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...
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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 ...
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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 ...
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06/25/2019
Perceptual Generative Autoencoders
Modern generative models are usually designed to match target distributi...
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10/30/2017
Understanding Hidden Memories of Recurrent Neural Networks
Recurrent neural networks (RNNs) have been successfully applied to vario...
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02/26/2017
