Optimization

Summary of Kingma & Welling's foundational VAE paper introducing the reparameterization trick and variational …...

Summary of Burda, Grosse & Salakhutdinov's ICLR 2016 paper introducing Importance Weighted Autoencoders for tighter …...

The key difference between multi-sample VAEs and IWAEs: how log-of-averages creates a tighter bound on log-likelihood.

A perspective paper defining the Grand Challenge of protein folding: distinguishing kinetic pathways from thermodynamic …...

The Müller-Brown potential: a classic 2D benchmark for optimization algorithms and reaction path methods....

Guide to implementing the Müller-Brown potential in PyTorch, comparing analytical vs automatic differentiation with …

Langevin dynamics simulation showing particle motion in the deep reactant minimum (Basin MA) of the Müller-Brown …

Langevin dynamics simulation showing particle motion in the product minimum (Basin MB) of the Müller-Brown potential …

GPU-accelerated PyTorch framework for the Müller-Brown potential with JIT compilation and Langevin dynamics....

Extended Langevin dynamics simulation showing particle transitions between different basins of the Müller-Brown …

Aneja et al.'s NeurIPS 2021 paper introducing Noise Contrastive Priors (NCPs) to address VAE's 'prior hole' problem with …...

Production-grade Word2Vec in PyTorch with vectorized Hierarchical Softmax, Negative Sampling, and torch.compile support....