A System for Model Diagnosis centered around Human Computation

Automatic feature discovery: A comparative study between filter and wrapper feature selection techniques

Encoding methods for categorical data: A comparative analysis for linear models, decision trees, and support vector machines

Filtering Knowledge: A Comparative Analysis of Information-Theoretical-Based Feature Selection Methods

Data-Driven Empirical Analysis of Correlation-Based Feature Selection Techniques

Graph Regularized Tensor Decomposition for Recommender Systems

Self-Supervised Few Shot Learning: Prototypical Contrastive Learning with Graphs

Deep Statistical Solver for Distribution System State Estimation

Hardware-based implementations in Side-Channel Analysis: A comparison study of DL SCA attacks against HW and SW AES and a novel methodology

Short-term Earthquake Prediction with Deep Neural Networks: Finding the optimal time prior to earthquake strikes to use in predictions

Improving cell type matching across species in scRNA-seq data using protein embeddings and transfer learning

Development of an LSTM-based methodology for burst detection in water distribution systems

How long before strike can we predict earthquakes with an LSTM neural network?

Assessing the Capability of Multimodal Variational Auto-Encoders in Combining Information From Biological Layers in Cancer Cells

Benchmarking the hyper-parameter sensitivity of VAE models for cancer treatment

Benchmarking VAE latent features in downstream tasks for cancer related predictions

Finding disentangled representations using VAE

The Effect of Different Initialization Methods on VAEs for Modeling Cancer using RNA Genome Expressions

Improving the Performance of Object Counting Using Training Images in the Frequency Domain

Combining frequency information and the unsupervisedW-Net model for wheat head detection