Müller-Brown Potential
The Müller-Brown potential: a classic two-dimensional analytical benchmark for testing optimization algorithms, reaction …...
Optimization
Implementing the Müller-Brown Potential in PyTorch
Guide to implementing the Müller-Brown potential in PyTorch, comparing analytical vs automatic differentiation with …
Müller-Brown Basin MA: Langevin Dynamics Simulation
Langevin dynamics simulation showing particle motion in the deep reactant minimum (Basin MA) of the Müller-Brown …
Müller-Brown Basin MB: Langevin Dynamics Simulation
Langevin dynamics simulation showing particle motion in the product minimum (Basin MB) of the Müller-Brown potential …
Müller-Brown Potential in PyTorch
PyTorch implementation of the Müller-Brown potential with performance optimizations, MD simulations, and analytical vs …...
Müller-Brown Transition: Langevin Dynamics Simulation
Extended Langevin dynamics simulation showing particle transitions between different basins of the Müller-Brown …
Modern PyTorch Techniques for VAEs: A Tutorial
VAE tutorial using modern PyTorch: torch.distributions, optimization techniques, numerical stability, and implementation …
Analytical Model of Word2Vec and GloVe Statistics
Analytical model of Word2Vec and GloVe statistics. First analytical solution to Word2Vec's softmax skip-gram with bias …...
EigenNoise: Data-Free Word Vector Initialization
Investigation into EigenNoise, a data-free initialization scheme for word vectors that approaches pre-trained model …...
A Framework for Multi-Arm Bandit Problems
Framework for understanding multi-arm bandit algorithms through five dimensions. Covers exploration vs exploitation and …
HyperNEAT: Scaling Neuroevolution with Geometric Patterns
How HyperNEAT uses indirect encoding and geometric patterns to evolve large-scale neural networks with biological …
NEAT: Evolving Neural Network Topologies
Learn about NEAT's approach to evolving neural networks: automatic topology design, historical markings, and speciation …