Bayesian methods for autonomous learning systems 

Novel optimization tools for structured signals recovery: channels estimation and compressible signal recovery 

Mode of visual perceptual learning: augmented Hebbian learning explains the function of feedback and beyond 

Emotional appraisal in deep reinforcement learning 

Data scarcity in robotics: leveraging structural priors and representation learning 

Efficient coding techniques for high definition video 

Adapting statistical learning for high risk scenarios 

Motor cortical representations of sensorimotor information during skill learning 

Learning contour statistics from natural images 

Scalable machine learning algorithms for item recommendation 

Point-based representations for 3D perception and reconstruction 

Learning shared subspaces across multiple views and modalities 

In/visible constituents: the representation of undocumented immigrants 

Effective graph representation and vertex classification with machine learning techniques 

Leveraging structure for learning robot control and reactive planning 

Multivariate statistical analysis of magnetoencephalography data 

Learning logical abstractions from sequential data 

Sample-efficient and robust neurosymbolic learning from demonstrations 

Modeling dynamic behaviors in the wild 

Active state learning from surprises in stochastic and partially-observable environments 

Neighborhood and graph constructions using non-negative kernel regression (NNK) 

Machine learning paradigms for behavioral coding 

Causality and consistency in electrophysiological signals 

LGBTQ+ representation in young children’s television: a qualitative research study 

The representation, learning, and control of dexterous motor skills in humans and humanoid robots