"molecular representation learning" Papers
14 papers found
Conference
3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko et al.
AAAI 2025paperarXiv:2309.04062
1
citations
Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations
Pengcheng Jiang, Cao Xiao, Tianfan Fu et al.
AAAI 2025paperarXiv:2306.01631
7
citations
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Evan Antoniuk, Shehtab Zaman, Tal Ben-Nun et al.
NEURIPS 2025arXiv:2505.01912
7
citations
DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
Yurou Liu, Jiahao Chen, Rui Jiao et al.
ICLR 2025
5
citations
Learning Molecular Representation in a Cell
Gang Liu, Srijit Seal, John Arevalo et al.
ICLR 2025arXiv:2406.12056
13
citations
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
Jingjing Hu, Dan Guo, Zhan Si et al.
AAAI 2025paperarXiv:2412.16483
6
citations
On the Expressive Power of Sparse Geometric MPNNs
Yonatan Sverdlov, Nadav Dym
ICLR 2025arXiv:2407.02025
6
citations
Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning
Gyoung S. Na, Chanyoung Park
ICLR 2025
Symmetry-Preserving Conformer Ensemble Networks for Molecular Representation Learning
Yanqiao Zhu, Yidan Shi, Yuanzhou Chen et al.
NEURIPS 2025
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
Tianlang Chen, Shengjie Luo, Di He et al.
ICML 2024arXiv:2406.16853
9
citations
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
Junwei Yang, Kangjie Zheng, Siyu Long et al.
ICML 2024
On the Generalization of Equivariant Graph Neural Networks
Rafał Karczewski, Amauri Souza, Vikas Garg
ICML 2024
SALSA: Semantically-Aware Latent Space Autoencoder
Kathryn Kirchoff, Travis Maxfield, Alexander Tropsha et al.
AAAI 2024paperarXiv:2310.02744
3
citations
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Shikun Feng, Yuyan Ni, Li et al.
ICML 2024arXiv:2405.10343
18
citations