Time Series Forecasting
Forecasting comparison of different neural architectures on the Multiscale Lorenz-96 system

Optimizing Sequence Models for Dynamical Systems

Ablation study deconstructing sequence models. Attention-augmented Recurrent Highway Networks outperform Transformers on …

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
Chemical structure from journal publication

GTR-CoT: Graph Traversal Chain-of-Thought for Molecules

GTR-CoT uses graph traversal chain-of-thought reasoning to improve optical chemical structure recognition accuracy.

Computational Chemistry
Markush structure diagram

SubGrapher: Visual Fingerprinting of Chemical Structures

Novel OCSR method creating molecular fingerprints from images through functional group segmentation for database …

Computational Chemistry
Chemical structure diagram for optical recognition

αExtractor: Chemical Info from Biomedical Literature

αExtractor uses ResNet-Transformer to extract chemical structures from literature images, including noisy and hand-drawn …

Computational Chemistry
Optical chemical structure recognition example

Img2Mol: Accurate SMILES from Molecular Depictions

Two-stage CNN approach for converting molecular images to SMILES using CDDD embeddings and extensive data augmentation.

Computational Chemistry
Markush structure diagram

MolNexTR: Generalized Deep Learning for Molecular Images

Chen et al.'s dual-stream encoder approach for robust molecular structure recognition from diverse real-world images …

Computational Chemistry
A colored molecule with annotations, representing the diverse drawing styles found in scientific papers that OCSR models must handle.

MolParser-7M & WildMol: Large-Scale OCSR Datasets

MolParser-7M is the largest OCSR dataset with 7.7M image-text pairs of molecules and E-SMILES, including 400k real-world …

Computational Chemistry
Optical chemical structure recognition example

MolParser: End-to-End Molecular Structure Recognition

MolParser converts molecular images from scientific documents to machine-readable formats using end-to-end learning.

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 …