Reading list for research topics in multimodal machine learning

MESS: Modern Electronic Structure Simulations

molSimplify code

A package to compute medical segmentation metrics.

Few-shot Learning and Similarity Graph Clustering for Automated Particle Analysis

aecroscopy

[ECCV2024] This is an official implementation for "PSALM: Pixelwise SegmentAtion with Large Multi-Modal Model"

Fastest Gephi's ForceAtlas2 graph layout algorithm implemented for Python and NetworkX

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

Atom_Probe

Help identify grain boundaries from atom probe datasets for mapping interfacial excesses and concentrations.

Graph-component approach to defect identification in large atomistic simulations

Codebase to accompany the paper A Look Inside the Black Box: Using Graph-Theoretical Descriptors to Interpret a Continuous-Filter Convolutional Neural Network (CF-CNN) trained on the Global and Loc…

HydroNet: Benchmark Tasks for Preserving Long-range Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data, at the 34th Conference on Neural Information Processin…

HydroNet: Benchmark Tasks for Preserving Long-range Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data, at the 34th Conference on Neural Information Processin…

Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators

An interesting application of gradient descent aims to stabilize any input graph such that the forces applied on each node are minimum and the overall model is stable. Visualization is perform usin…

Fast and Accurate Predictions from 3D Molecular Structures

A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.

Molecular Hypergraph Neural Network

Creating a heatmap based on video recordings

Code for the NeurIPS 2019 paper: Topology-Preserving Deep Image Segmentation

Parallel version of Hydronet

AI4Chem is a code to test the ability of large language models (ChatGPT) to comprehend Chemistry.

DefectSegNet for semantic segmentation of defects in Steels

Database, dimensionality reduction, and visualization dashboard for RHEED data