
Improving Generalization and Stability of Generative Adversarial Networks
Generative Adversarial Networks (GANs) are one of the most popular tools...
read it

Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework
Reinforcement learning (RL) has emerged as a standard approach for build...
read it

Distributionally Robust Bayesian Quadrature Optimization
Bayesian quadrature optimization (BQO) maximizes the expectation of an e...
read it

Spoof Face Detection Via SemiSupervised Adversarial Training
Face spoofing causes severe security threats in face recognition systems...
read it

SelfAssttentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
read it

SelfAttentive Associative Memory
Heretofore, neural networks with external memory are restricted to singl...
read it

Interpretable and Efficient Heterogeneous Graph Convolutional Network
Graph Convolutional Network (GCN) has achieved extraordinary success in ...
read it

SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity
Deeper convolutional neural networks provide more capacity to approximat...
read it

Bayesian functional optimisation with shape prior
Real world experiments are expensive, and thus it is important to reach ...
read it

Towards effective AIpowered agile project management
The rise of Artificial intelligence (AI) has the potential to significan...
read it

PIRM2018 Challenge on Spectral Image SuperResolution: Dataset and Study
This paper introduces a newly collected and novel dataset (StereoMSI) fo...
read it

Theory and Evaluation Metrics for Learning Disentangled Representations
We make two theoretical contributions to disentanglement learning by (a)...
read it

Superresolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
This paper introduces a novel method to simultaneously superresolve and...
read it

Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos
Appearance features have been widely used in video anomaly detection eve...
read it

Explicit Facial Expression Transfer via FineGrained Semantic Representations
Facial expression transfer between two unpaired images is a challenging ...
read it

A Visual Communication Map for MultiAgent Deep Reinforcement Learning
Multiagent learning distinctly poses significant challenges in the effo...
read it

Learning to Remember More with Less Memorization
Memoryaugmented neural networks consisting of a neural controller and a...
read it

KernelFree Image Deblurring with a Pair of Blurred/Noisy Images
Complex blur like the mixup of spacevariant and spaceinvariant blur, w...
read it

Learning to Reason with Relational Video Representation for Question Answering
How does machine learn to reason about the content of a video in answeri...
read it

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling
Scientific experiments are usually expensive due to complex experimental...
read it

Incorporating Expert Prior in Bayesian Optimisation via Space Warping
Bayesian optimisation is a wellknown sampleefficient method for the op...
read it

MultiAgent Deep Reinforcement Learning with Human Strategies
Deep learning has enabled traditional reinforcement learning methods to ...
read it

On catastrophic forgetting and mode collapse in Generative Adversarial Networks
Generative Adversarial Networks (GAN) are one of the most prominent tool...
read it

Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics
Device fingerprints like sensor pattern noise (SPN) are widely used for ...
read it

HDF: Hybrid Deep Features for Scene Image Representation
Nowadays it is prevalent to take features extracted from pretrained dee...
read it

Automatic feature learning for vulnerability prediction
Code flaws or vulnerabilities are prevalent in software systems and can ...
read it

KGAN: How to Break The Minimax Game in GAN
Generative Adversarial Networks (GANs) were intuitively and attractively...
read it

Creating a Social Brain for Cooperative Connected Autonomous Vehicles: Issues and Challenges
The connected autonomous vehicle has been often touted as a technology t...
read it

Geometric Enclosing Networks
Training model to generate data has increasingly attracted research atte...
read it

MultiGenerator Generative Adversarial Nets
We propose a new approach to train the Generative Adversarial Nets (GANs...
read it

Analogicalbased Bayesian Optimization
Some realworld problems revolve to solve the optimization problem _x∈Xf...
read it

Dual Discriminator Generative Adversarial Nets
We propose in this paper a novel approach to tackle the problem of mode ...
read it

Faster Training of Very Deep Networks Via pNorm Gates
A major contributing factor to the recent advances in deep neural networ...
read it

Statistical Latent Space Approach for Mixed Data Modelling and Applications
The analysis of mixed data has been raising challenges in statistics and...
read it

Wind ramp event prediction with parallelized Gradient Boosted Regression Trees
Accurate prediction of wind ramp events is critical for ensuring the rel...
read it

A Random Finite Set Model for Data Clustering
The goal of data clustering is to partition data points into groups to m...
read it

Robust artificial neural networks and outlier detection. Technical report
Large outliers break down linear and nonlinear regression models. Robust...
read it

Stabilizing Linear Prediction Models using Autoencoder
To date, the instability of prognostic predictors in a sparse high dimen...
read it

A deep learning model for estimating story points
Although there has been substantial research in software analytics for e...
read it

A deep language model for software code
Existing language models such as ngrams for software code often fail to...
read it

DeepSoft: A vision for a deep model of software
Although software analytics has experienced rapid growth as a research a...
read it

Preterm Birth Prediction: Deriving Stable and Interpretable Rules from High Dimensional Data
Preterm births occur at an alarming rate of 1015 risk of infant mortali...
read it

An evaluation of randomized machine learning methods for redundant data: Predicting short and mediumterm suicide risk from administrative records and risk assessments
Accurate prediction of suicide risk in mental health patients remains an...
read it

Approximation Vector Machines for Largescale Online Learning
One of the most challenging problems in kernel online learning is to bou...
read it

Weakly monotone averaging functions
Monotonicity with respect to all arguments is fundamental to the definit...
read it

Treebased iterated local search for Markov random fields with applications in image analysis
The maximum a posteriori (MAP) assignment for general structure Markov r...
read it

Collaborative filtering via sparse Markov random fields
Recommender systems play a central role in providing individualized acce...
read it

A Robust 3D2D Interactive Tool for Scene Segmentation and Annotation
Recent advances of 3D acquisition devices have enabled largescale acqui...
read it

MultiResidual Networks: Improving the Speed and Accuracy of Residual Networks
In this article, we take one step toward understanding the learning beha...
read it

MixedVariate Restricted Boltzmann Machines
Modern datasets are becoming heterogeneous. To this end, we present in t...
read it
Deakin University
Discover Deakin University. We are a progressive and openminded university, with the highest student satisfaction in Victoria. Find out why now.