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05/11/2023
Towards Understanding and Improving GFlowNet Training
Generative flow networks (GFlowNets) are a family of algorithms that lea...
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10/21/2022
Conditional Diffusion with Less Explicit Guidance via Model Predictive Control
How much explicit guidance is necessary for conditional diffusion? We co...
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08/05/2022
Parameter Averaging for Robust Explainability
Neural Networks are known to be sensitive to initialisation. The explana...
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03/15/2022
MoReL: Multi-omics Relational Learning
Multi-omics data analysis has the potential to discover hidden molecular...
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12/15/2021
Bayesian Graph Contrastive Learning
Contrastive learning has become a key component of self-supervised learn...
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10/08/2021
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
Self-supervised learning has been shown to be very effective in learning...
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08/28/2021
Tracing app technology: An ethical review in the COVID-19 era and directions for post-COVID-19
We conducted a systematic literature review on the ethical consideration...
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04/04/2021
SimCD: Simultaneous Clustering and Differential expression analysis for single-cell transcriptomic data
Single-Cell RNA sequencing (scRNA-seq) measurements have facilitated gen...
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10/12/2020
BayReL: Bayesian Relational Learning for Multi-omics Data Integration
High-throughput molecular profiling technologies have produced high-dime...
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06/07/2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling
We propose a unified framework for adaptive connection sampling in graph...
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10/28/2019
Semi-Implicit Stochastic Recurrent Neural Networks
Stochastic recurrent neural networks with latent random variables of com...
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08/26/2019
Variational Graph Recurrent Neural Networks
Representation learning over graph structured data has been mostly studi...
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08/19/2019
Semi-Implicit Graph Variational Auto-Encoders
Semi-implicit graph variational auto-encoder (SIG-VAE) is proposed to ex...
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02/12/2019
A Novel Maneuvering Target Tracking Approach by Stochastic Volatility GARCH Model
In this paper, we introduce a new single model maneuvering target tracki...
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02/12/2019
Non-Linear Non-Stationary Heteroscedasticity Volatility for Tracking of Jump Processes
In this paper, we introduce a new jump process modeling which involves a...
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02/08/2019
Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty
Single-cell gene expression measurements offer opportunities in deriving...
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10/22/2018
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data
Precision medicine aims for personalized prognosis and therapeutics by u...
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03/07/2018