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Generative-Models

Scientific Computing
Grid of complex molecular structures rendered from SELFIES and SMILES strings

Molecular String Renderer: Robust Visualization Tool

A robust, type-safe Python library for converting chemical strings (SMILES, SELFIES, InChI) into publication-quality …

Generative Modeling
Diagram comparing standard stochastic sampling (gradient blocked) vs the reparameterization trick (gradient flows)

Auto-Encoding Variational Bayes (VAE Paper Summary)

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

Generative Modeling
MNIST digit samples generated from a Variational Autoencoder latent space

Importance Weighted Autoencoders: Beyond the Standard VAE

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

Generative Modeling
Flowchart comparing VAE and IWAE computation showing the key difference in where averaging occurs relative to the log operation

IWAE: Importance Weighted Autoencoders

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

Computational Chemistry
Benzene in SELFIES notation

Recent Advances in the SELFIES Library (2023)

Major updates to the SELFIES library, improved performance, expanded chemistry support, and new customization features.

Computational Chemistry
SELFIES molecular representation overview

SELFIES: The Original Paper (Krenn et al. 2020)

The 2020 paper introducing SELFIES, the 100% robust molecular representation that solves SMILES validity problems in ML …

Computational Chemistry
SELFIES strings guarantee 100% valid molecules - even when generated randomly

Converting SELFIES Strings to 2D Molecular Images

Visualize SELFIES molecular representations and test their 100% robustness through random sampling experiments.

Computational Chemistry
SELFIES representation of 2-Fluoroethenimine molecule

SELFIES (Self-Referencing Embedded Strings)

SELFIES is a 100% robust molecular string representation for ML, implemented in the open-source selfies Python library.

Computational Chemistry
Potential energy surface showing molecular conformation space with equilibrium and low energy conformations

DenoiseVAE: Adaptive Noise for Molecular Pre-training

Liu et al.'s ICLR 2025 paper introducing DenoiseVAE, which learns adaptive, atom-specific noise for better molecular …

Generative Modeling
Visualization of the VAE prior hole problem showing a ring-shaped aggregate posterior with an empty center where the Gaussian prior has highest density

Contrastive Learning for Variational Autoencoder Priors

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

Computational Chemistry
SELFIES robustness demonstration

Invalid SMILES Benefit Chemical Language Models: A Study

Skinnider (2024) shows that generating invalid SMILES actually improves chemical language model performance through …

Generative Modeling
Variational Autoencoder architecture diagram showing encoder, latent space, and decoder

Modern PyTorch Techniques for VAEs: A Hands-On Tutorial

Learn to implement VAEs in PyTorch: ELBO objective, reparameterization trick, loss scaling, and MNIST experiments on …