Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks

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Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks

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Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Random matrix methods for high-dimensional machine learning models

Learning to Reason with Neural Networks: Principles and Methods

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy

Robust machine learning for neuroscientific inference

Weighting Pseudo-labels via High-Activation Feature Index Similarity and Object Detection for Semi-supervised Segmentation

Topics in statistical physics of high-dimensional machine learning

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Safe Deep Neural Networks

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

A comparative analysis of gene expression profiling by statistical and machine learning approaches

Machine Learning for Modeling Stock Returns

Computational design of complex protein folds and soluble analogs of membrane proteins

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Sequential Reasoning with Socially Caused Beliefs