Generative adversarial training of product of policies for robust and adaptive movement primitives

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Generative adversarial training of product of policies for robust and adaptive movement primitives

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Understanding generalization and robustness in modern deep learning

Topics in statistical physics of high-dimensional machine learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Robust machine learning for neuroscientific inference

Residual-based attention in physics-informed neural networks

Machine learning-aided generative molecular design

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

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

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Robust NAS under adversarial training: benchmark, theory, and beyond

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

On the Generalization of Stochastic Gradient Descent with Momentum

Incorporating Projective Geometry into Deep Learning

Random matrix methods for high-dimensional machine learning models

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

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Meta-learning to address diverse Earth observation problems across resolutions