Physics of Biological Systems

Related lectures (34)

Explores the use of optics in machine learning, focusing on large-scale random matrix multiplication through multiple scattering of light.

Explores the statistical mechanics of learning, focusing on neural networks' mysteries and computational challenges.

Covers mathematical modeling in chemistry and biology, including chemical reactions, enzymatic kinetics, and population dynamics.

Explores large scale stability in dynamical systems and interconnected behavior.

Covers general aspects and techniques of microscopy, emphasizing resolution importance and exploring scanning tunneling and atomic force microscopy.

Explores Systems Biology, metabolic pathways, genome-scale models, and bioinformatic tools for predictive biochemistry in bioproduction.

Covers the fundamentals of multi-layer neural networks and the training process of fully connected networks with hidden layers.

Explores the training and optimization of neural networks, addressing challenges like non-convex loss functions and local minima.

Explores Newton's method for dynamical systems, GMRES, FGMRES, optimization, multishooting, and trust-region methods.

Explores language detection using Recurrent Neural Networks and supervised learning concepts.

Delves into protein polymers, discussing co-evolution, diffusion, protein structures, and experimental methods.

Covers the role of Transformers in unifying various machine learning fields.

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