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07/24/2023
Towards Generalising Neural Topical Representations
Topic models have evolved from conventional Bayesian probabilistic model...
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07/15/2023
Multiscale Memory Comparator Transformer for Few-Shot Video Segmentation
Few-shot video segmentation is the task of delineating a specific novel ...
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05/25/2023
Learning Directed Graphical Models with Optimal Transport
Estimating the parameters of a probabilistic directed graphical model fr...
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04/26/2023
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization
Deep learning models, even the-state-of-the-art ones, are highly vulnera...
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04/12/2023
MED-VT: Multiscale Encoder-Decoder Video Transformer with Application to Object Segmentation
Multiscale video transformers have been explored in a wide variety of vi...
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04/04/2023
Multimodal Neural Processes for Uncertainty Estimation
Neural processes (NPs) have brought the representation power of parametr...
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02/20/2023
Transformed Distribution Matching for Missing Value Imputation
We study the problem of imputing missing values in a dataset, which has ...
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02/12/2023
Vector Quantized Wasserstein Auto-Encoder
Learning deep discrete latent presentations offers a promise of better s...
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10/09/2022
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport
Few-shot classification aims to learn a classifier to recognize unseen c...
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10/06/2022
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture
Uncertainty estimation is essential to make neural networks trustworthy ...
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09/27/2022
Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations
Interpretable machine learning seeks to understand the reasoning process...
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08/09/2022
Sports Video Analysis on Large-Scale Data
This paper investigates the modeling of automated machine description on...
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08/05/2022
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification
Imbalanced data pose challenges for deep learning based classification m...
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05/04/2022
P3IV: Probabilistic Procedure Planning from Instructional Videos with Weak Supervision
In this paper, we study the problem of procedure planning in instruction...
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03/03/2022
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
A topic model is often formulated as a generative model that explains ho...
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02/27/2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
It is well-known that deep neural networks (DNNs) are susceptible to adv...
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10/14/2021
Neural Attention-Aware Hierarchical Topic Model
Neural topic models (NTMs) apply deep neural networks to topic modelling...
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07/11/2021
Review of Video Predictive Understanding: Early Action Recognition and Future Action Prediction
Video predictive understanding encompasses a wide range of efforts that ...
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07/11/2021
Interpretable Deep Feature Propagation for Early Action Recognition
Early action recognition (action prediction) from limited preliminary ob...
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04/27/2021
Improved and Efficient Text Adversarial Attacks using Target Information
There has been recently a growing interest in studying adversarial examp...
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02/28/2021
Topic Modelling Meets Deep Neural Networks: A Survey
Topic modelling has been a successful technique for text analysis for al...
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01/25/2021
Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning
Contrastive learning (CL) has recently emerged as an effective approach ...
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10/14/2020
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability
Training robust deep learning models for down-stream tasks is a critical...
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10/13/2020
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images
Deep neural network image classifiers are reported to be susceptible to ...
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09/21/2020
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness
Ensemble-based adversarial training is a principled approach to achieve ...
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08/12/2020
Neural Sinkhorn Topic Model
In this paper, we present a new topic modelling approach via the theory ...
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08/06/2020
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models
Deep neural network based image classification methods usually require a...
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07/17/2020
SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression
Obtaining training data for multi-document summarization (MDS) is time c...
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07/10/2020
Improving Adversarial Robustness by Enforcing Local and Global Compactness
The fact that deep neural networks are susceptible to crafted perturbati...
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02/21/2020
Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering
Matrix factorization (MF) has been widely applied to collaborative filte...
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10/03/2019
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions
Deep neural network image classifiers are reported to be susceptible to ...
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08/16/2019
daBNN: A Super Fast Inference Framework for Binary Neural Networks on ARM devices
It is always well believed that Binary Neural Networks (BNNs) could dras...
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05/02/2019
Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data
Many applications, such as text modelling, high-throughput sequencing, a...
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04/10/2019
Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification
Re-identifying a person across multiple disjoint camera views is importa...
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11/02/2018
Dirichlet belief networks for topic structure learning
Recently, considerable research effort has been devoted to developing de...
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05/08/2018
A Transfer Learning Approach for Microstructure Reconstruction and Structure-property Predictions
Stochastic microstructure reconstruction has become an indispensable par...
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09/19/2017
MetaLDA: a Topic Model that Efficiently Incorporates Meta information
Besides the text content, documents and their associated words usually c...
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06/14/2017
Leveraging Node Attributes for Incomplete Relational Data
Relational data are usually highly incomplete in practice, which inspire...
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06/07/2017
