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09/07/2023
TSGBench: Time Series Generation Benchmark
Synthetic Time Series Generation (TSG) is crucial in a range of applicat...
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08/31/2023
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
To handle graphs in which features or connectivities are evolving over t...
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08/22/2023
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?
The Potential Outcome Framework (POF) plays a prominent role in the fiel...
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08/02/2023
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference
Causal inference plays a vital role in diverse domains like epidemiology...
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07/24/2023
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network
Counterfactual inference for continuous rather than binary treatment var...
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02/21/2023
Lightweight-Yet-Efficient: Revitalizing Ball-Tree for Point-to-Hyperplane Nearest Neighbor Search
Finding the nearest neighbor to a hyperplane (or Point-to-Hyperplane Nea...
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02/03/2023
Simple, Effective and General: A New Backbone for Cross-view Image Geo-localization
In this work, we aim at an important but less explored problem of a simp...
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01/15/2023
Improving Reliability of Fine-tuning with Block-wise Optimisation
Finetuning can be used to tackle domain-specific tasks by transferring k...
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11/23/2022
SAH: Shifting-aware Asymmetric Hashing for Reverse k-Maximum Inner Product Search
This paper investigates a new yet challenging problem called Reverse k-M...
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02/22/2022
DIOT: Detecting Implicit Obstacles from Trajectories
In this paper, we study a new data mining problem of obstacle detection ...
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09/21/2021
Unsupervised Abstract Reasoning for Raven's Problem Matrices
Raven's Progressive Matrices (RPM) is highly correlated with human intel...
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06/19/2021
A Generic Distributed Clustering Framework for Massive Data
In this paper, we introduce a novel Generic distributEd clustEring frame...
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10/29/2020
T-vectors: Weakly Supervised Speaker Identification Using Hierarchical Transformer Model
Identifying multiple speakers without knowing where a speaker's voice is...
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10/21/2020
Improving Audio Anomalies Recognition Using Temporal Convolutional Attention Network
Anomalous audio in speech recordings is often caused by speaker voice di...
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05/16/2020
Exploration of Audio Quality Assessment and Anomaly Localisation Using Attention Models
Many applications of speech technology require more and more audio data....
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05/15/2020
Speaker Re-identification with Speaker Dependent Speech Enhancement
While the use of deep neural networks has significantly boosted speaker ...
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05/15/2020
Weakly Supervised Training of Hierarchical Attention Networks for Speaker Identification
Identifying multiple speakers without knowing where a speaker's voice is...
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04/11/2020
Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring
Locality-Sensitive Hashing (LSH) is one of the most popular methods for ...
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01/17/2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks
Graph structured data has wide applicability in various domains such as ...
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01/14/2020
Robust Speaker Recognition Using Speech Enhancement And Attention Model
In this paper, a novel architecture for speaker recognition is proposed ...
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11/18/2019
Multi-task Sentence Encoding Model for Semantic Retrieval in Question Answering Systems
Question Answering (QA) systems are used to provide proper responses to ...
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10/17/2019
H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical Attention Model
In this paper, a hierarchical attention network to generate utterance-le...
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10/16/2019
Contextual Joint Factor Acoustic Embeddings
Embedding acoustic information into fixed length representations is of i...
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09/24/2019
Improving Robustness In Speaker Identification Using A Two-Stage Attention Model
In this paper a novel framework to tackle speaker recognition using a tw...
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02/24/2017
Convolutional Gated Recurrent Neural Network Incorporating Spatial Features for Audio Tagging
Environmental audio tagging is a newly proposed task to predict the pres...
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07/13/2016
Hierarchical learning for DNN-based acoustic scene classification
In this paper, we present a deep neural network (DNN)-based acoustic sce...
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07/13/2016
Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging
Environmental audio tagging aims to predict only the presence or absence...
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06/24/2016