chom5621's Stars
ml-postech/HUB
Official implementation of "Holistic Unlearning Benchmark: A Multi-Faceted Evaluation for Text-to-Image Diffusion Model Unlearning"
CMACH508/KGDiff
Towards Explainable Target-Aware Molecule Generation with Knowledge Guidance
samuelmurail/docking_py
Docking_py is a python library allowing a simplified use of the Smina, vina, qvina2 and qvinaw docking software. Docking_py can be easily automatize and scripted.
joshchang1112/bert_gnn_arxiv
Multi-class Classification with fine-tuned BERT & GNN
plotly/dash-cytoscape
Interactive network visualization in Python and Dash, powered by Cytoscape.js
dylanhogg/llmgraph
Create knowledge graphs with LLMs
viswavi/few-shot-clustering
DavidMcDonald1993/cobdock
Reference implementation of the COBDock algorithm.
kyegomez/AlphaFold3
Implementation of Alpha Fold 3 from the paper: "Accurate structure prediction of biomolecular interactions with AlphaFold3" in PyTorch
AlgoMole/MolCRAFT
Implementation for ICML 2024 paper "MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space"
maabuu/posebusters
Plausibility checks for generated molecule poses.
hwwang55/MolR
Chemical-Reaction-Aware Molecule Representation Learning
YangLing0818/BindDM
[AAAI 2024] Binding-Adaptive Diffusion Models for Structure-Based Drug Design
guanjq/targetdiff
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
YangLing0818/IPDiff
[ICLR 2024] Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
ml-postech/MetaSSD
Meta-Learned Self-Supervised Detection
ml-postech/RoWN
Official PyTorch implementation of "A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning"
ml-postech/SpReME
ml-postech/Skeleton-anonymization
Official implementation of 'Anonymization for Skeleton Action Recognition'
ml-postech/TTEN
[CIKM'23] Test Time Embedding Normalization for Popularity Bias Mitigation
ml-postech/GM-VAE
Official PyTorch implementation of "Hyperbolic VAE via Latent Gaussian Distributions"