Texas A&M University

∙ College Station , United States ∙ 0 followers

Texas A&M University is a coeducational public research university in College Station, Texas, United States.

Kronecker Attention Networks

Attention operators have been applied on both 1-D data like texts and hi...
07/16/2020 ∙ by Hongyang Gao, et al. ∙ 54 ∙ share

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Focus Longer to See Better:Recursively Refined Attention for Fine-Grained Image Classification

Deep Neural Network has shown great strides in the coarse-grained image ...
05/22/2020 ∙ by Prateek Shroff, et al. ∙ 50 ∙ share

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PyODDS: An End-to-End Outlier Detection System

PyODDS is an end-to end Python system for outlier detection with databas...
10/07/2019 ∙ by Yuening Li, et al. ∙ 41 ∙ share

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XGNN: Towards Model-Level Explanations of Graph Neural Networks

Graphs neural networks (GNNs) learn node features by aggregating and com...
06/03/2020 ∙ by Hao Yuan, et al. ∙ 39 ∙ share

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Non-Local Graph Neural Networks

Modern graph neural networks (GNNs) learn node embeddings through multil...
05/29/2020 ∙ by Meng Liu, et al. ∙ 34 ∙ share

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Deep Learning of High-Order Interactions for Protein Interface Prediction

Protein interactions are important in a broad range of biological proces...
07/18/2020 ∙ by YI LIU, et al. ∙ 26 ∙ share

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Score-CAM:Improved Visual Explanations Via Score-Weighted Class Activation Mapping

Recently, more and more attention has been drawn into the internal mecha...
10/03/2019 ∙ by Haofan Wang, et al. ∙ 25 ∙ share

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Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models

Inverse problems are pervasive mathematical methods in inferring knowled...
12/17/2019 ∙ by Sheroze Sheriffdeen, et al. ∙ 20 ∙ share

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Machine Learning Explanations to Prevent Overtrust in Fake News Detection

Combating fake news and misinformation propagation is a challenging task...
07/24/2020 ∙ by Sina Mohseni, et al. ∙ 16 ∙ share

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Graph Contrastive Learning with Augmentations

Generalizable, transferrable, and robust representation learning on grap...
10/22/2020 ∙ by Yuning You, et al. ∙ 13 ∙ share

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Network-principled deep generative models for designing drug combinations as graph sets

Combination therapy has shown to improve therapeutic efficacy while redu...
04/16/2020 ∙ by Mostafa Karimi, et al. ∙ 12 ∙ share

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EventPlus: A Temporal Event Understanding Pipeline

We present EventPlus, a temporal event understanding pipeline that integ...
01/13/2021 ∙ by Mingyu Derek Ma, et al. ∙ 12 ∙ share

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AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Neural architecture search (NAS) has witnessed prevailing success in ima...
08/11/2019 ∙ by Xinyu Gong, et al. ∙ 10 ∙ share

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On the Search for Feedback in Reinforcement Learning

This paper addresses the problem of learning the optimal feedback policy...
02/21/2020 ∙ by Ran Wang, et al. ∙ 10 ∙ share

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Learning an Interpretable Traffic Signal Control Policy

Signalized intersections are managed by controllers that assign right of...
12/23/2019 ∙ by James Ault, et al. ∙ 9 ∙ share

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Deep Structured Cross-Modal Anomaly Detection

Anomaly detection is a fundamental problem in data mining field with man...
08/11/2019 ∙ by Yuening Li, et al. ∙ 8 ∙ share

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I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively

The learning of hierarchical representations for image classification ha...
02/25/2020 ∙ by Haotao Wang, et al. ∙ 7 ∙ share

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DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better

We present a new end-to-end generative adversarial network (GAN) for sin...
08/10/2019 ∙ by Orest Kupyn, et al. ∙ 6 ∙ share

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Topology-Aware Graph Pooling Networks

Pooling operations have shown to be effective on computer vision and nat...
10/19/2020 ∙ by Hongyang Gao, et al. ∙ 6 ∙ share

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Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

In recent years, unfolding iterative algorithms as neural networks has b...
08/29/2018 ∙ by Xiaohan Chen, et al. ∙ 5 ∙ share

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Acceleration of Radiation Transport Solves Using Artificial Neural Networks

Discontinuous Finite Element Methods (DFEM) have been widely used for so...
06/06/2019 ∙ by Mauricio Tano, et al. ∙ 5 ∙ share

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A Hybrid Deep Learning Model for Predictive Flood Warning and Situation Awareness using Channel Network Sensors Data

The objective of this study is to create and test a hybrid deep learning...
06/15/2020 ∙ by Shangjia Dong, et al. ∙ 5 ∙ share

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Generative and Discriminative Learning for Distorted Image Restoration

Liquify is a common technique for image editing, which can be used for i...
11/11/2020 ∙ by Yi Gu, et al. ∙ 5 ∙ share

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DAVID: Dual-Attentional Video Deblurring

Blind video deblurring restores sharp frames from a blurry sequence with...
12/07/2019 ∙ by Junru Wu, et al. ∙ 4 ∙ share

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Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising

Self-supervised frameworks that learn denoising models with merely indiv...
10/22/2020 ∙ by Yaochen Xie, et al. ∙ 4 ∙ share

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Network Shrinkage Estimation

Networks are a natural representation of complex systems across the scie...
08/02/2019 ∙ by Nesreen K. Ahmed, et al. ∙ 3 ∙ share

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RLCard: A Toolkit for Reinforcement Learning in Card Games

RLCard is an open-source toolkit for reinforcement learning research in ...
10/10/2019 ∙ by Daochen Zha, et al. ∙ 2 ∙ share

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Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion

We present our preliminary work to determine if patient's vocal acoustic...
11/29/2017 ∙ by Aven Samareh, et al. ∙ 1 ∙ share

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End-to-End United Video Dehazing and Detection

The recent development of CNN-based image dehazing has revealed the effe...
09/12/2017 ∙ by Boyi Li, et al. ∙ 1 ∙ share

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Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

Emotion recognition from facial expressions is tremendously useful, espe...
09/10/2017 ∙ by Bowen Cheng, et al. ∙ 1 ∙ share

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Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study

This paper aims to improve privacy-preserving visual recognition, an inc...
07/22/2018 ∙ by Zhenyu Wu, et al. ∙ 1 ∙ share

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Privacy-Preserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset

This paper aims to boost privacy-preserving visual recognition, an incre...
06/12/2019 ∙ by Haotao Wang, et al. ∙ 1 ∙ share

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AutoSpeech: Neural Architecture Search for Speaker Recognition

Speaker recognition systems based on Convolutional Neural Networks (CNNs...
05/07/2020 ∙ by Shaojin Ding, et al. ∙ 1 ∙ share

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Incentivizing Sharing in Realtime D2D Streaming Networks: A Mean Field Game Perspective

We consider the problem of streaming live content to a cluster of co-loc...
04/08/2016 ∙ by Jian Li, et al. ∙ 0 ∙ share

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Tensor Completion Algorithms in Big Data Analytics

Tensor completion is a problem of filling the missing or unobserved entr...
11/28/2017 ∙ by Qingquan Song, et al. ∙ 0 ∙ share

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Throughput Optimal Decentralized Scheduling of Multi-Hop Networks with End-to-End Deadline Constraints: II Wireless Networks with Interference

Consider a multihop wireless network serving multiple flows in which wir...
09/06/2017 ∙ by Rahul Singh, et al. ∙ 0 ∙ share

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Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions

The key idea of variational auto-encoders (VAEs) resembles that of tradi...
05/18/2017 ∙ by Zhengyang Wang, et al. ∙ 0 ∙ share

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Approximating Continuous Functions by ReLU Nets of Minimal Width

This article concerns the expressive power of depth in deep feed-forward...
10/31/2017 ∙ by Boris Hanin, et al. ∙ 0 ∙ share

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α-Variational Inference with Statistical Guarantees

We propose a variational approximation to Bayesian posterior distributio...
10/09/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Visual Servoing of Unmanned Surface Vehicle from Small Tethered Unmanned Aerial Vehicle

This paper presents an algorithm and the implementation of a motor schem...
10/09/2017 ∙ by Haresh Karnan, et al. ∙ 0 ∙ share

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Evolutionary Approaches to Optimization Problems in Chimera Topologies

Chimera graphs define the topology of one of the first commercially avai...
08/17/2016 ∙ by Roberto Santana, et al. ∙ 0 ∙ share

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Frequentist coverage and sup-norm convergence rate in Gaussian process regression

Gaussian process (GP) regression is a powerful interpolation technique d...
08/16/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

This article concerns the expressive power of depth in neural nets with ...
08/09/2017 ∙ by Boris Hanin, et al. ∙ 0 ∙ share

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Attributed Network Embedding for Learning in a Dynamic Environment

Network embedding leverages the node proximity manifested to learn a low...
06/06/2017 ∙ by Jundong Li, et al. ∙ 0 ∙ share

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Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs

This paper is concerned with the problem of stochastic control of gene r...
02/24/2017 ∙ by Mahdi Imani, et al. ∙ 0 ∙ share

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Surrogate Aided Unsupervised Recovery of Sparse Signals in Single Index Models for Binary Outcomes

We consider the recovery of regression coefficients, denoted by β_0, for...
01/18/2017 ∙ by Abhishek Chakrabortty, et al. ∙ 0 ∙ share

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Detection of Cooperative Interactions in Logistic Regression Models

An important problem in the field of bioinformatics is to identify inter...
02/12/2016 ∙ by Easton Li Xu, et al. ∙ 0 ∙ share

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Data Integration with High Dimensionality

We consider a problem of data integration. Consider determining which ge...
10/03/2016 ∙ by Xin Gao, et al. ∙ 0 ∙ share

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Functorial Hierarchical Clustering with Overlaps

This work draws its inspiration from three important sources of research...
09/08/2016 ∙ by Jared Culbertson, et al. ∙ 0 ∙ share

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Consistency constraints for overlapping data clustering

We examine overlapping clustering schemes with functorial constraints, i...
08/15/2016 ∙ by Jared Culbertson, et al. ∙ 0 ∙ share

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