Deep Generative Models in Drug Discovery

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Fragment-Based Drug Discovery: Concepts & Technologies

Covers the concepts and technologies of fragment-based drug discovery, exploring hit identification, lead optimization, and screening methods.

Interrogating SAR in Medical Chemistry

Delves into the fundamentals of medicinal chemistry, emphasizing the interrogation of Structure-Activity Relationships (SAR) in drug design.

Structures in Non-Convex Optimization

Covers non-convex optimization, deep learning training problems, stochastic gradient descent, adaptive methods, and neural network architectures.

Optimisation in Energy Systems

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

The Hidden Convex Optimization Landscape of Deep Neural Networks

Explores the hidden convex optimization landscape of deep neural networks, showcasing the transition from non-convex to convex models.

Neural Networks Optimization

Explores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.

Neuroscience and AI: Bridging the Gap

Explores the gap between AI and human intelligence through neuroscience-inspired models and algorithms.

Automating Scanning Probe Microscopy: Techniques and Applications

Covers the integration of machine learning with scanning probe microscopy for enhanced automation and efficiency in scientific workflows.

Deep and Robust Reinforcement Learning Techniques

Discusses advanced reinforcement learning techniques, focusing on deep and robust methods, including actor-critic frameworks and adversarial learning strategies.

Optimization Techniques: Convexity in Machine Learning

Covers optimization techniques in machine learning, focusing on convexity and its implications for efficient problem-solving.