Bayesian multitask inverse reinforcement learning

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In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

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Bayesian multitask inverse reinforcement learning

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Incorporating Projective Geometry into Deep Learning

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Social Opinion Formation and Decision Making Under Communication Trends

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Unveiling the complexity of learning and decision-making

Predicting the long-term collective behaviour of fish pairs with deep learning

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Topics in statistical physics of high-dimensional machine learning

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

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

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Computational models of intrinsic motivation for curiosity and creativity

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

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

Safe Deep Neural Networks

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Residual-based attention in physics-informed neural networks

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

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