molecular representation

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Most implemented papers archive 2025-07-28

30 shown of 87 papers with code (168 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs
  18 Jul 2022 5 repositories listed Syntology ran 6 of 6 samples · 0 unverified
  Pretraining molecular representation models without labels is fundamental to various applications.
• Analyzing Learned Molecular Representations for Property Prediction
  2 Apr 2019 4 repositories listed Syntology ran 3 of 15 samples · 12 unverified
  In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary…
• ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
  19 Oct 2020 3 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  GNNs and chemical fingerprints are the predominant approaches to representing molecules for property prediction.
• Self-Supervised Graph Transformer on Large-Scale Molecular Data
  18 Jun 2020 3 repositories listed
  We pre-train GROVER with 100 million parameters on 10 million unlabelled molecules -- the biggest GNN and the largest training dataset in molecular representation learning.
• The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMA
  2 May 2024 2 repositories listed
  However, we observed that absolute validation loss is not a definitive indicator of model performance - contradicts previous research - at least for fine-tuning tasks: instead, model size plays a crucial role.
• Can Large Language Models Understand Molecules?
  5 Jan 2024 2 repositories listed
  Notably, LLaMA-based SMILES embeddings show results comparable to pre-trained models on SMILES in molecular prediction tasks and outperform the pre-trained models for the DDI prediction tasks.
• Uncovering Neural Scaling Laws in Molecular Representation Learning
  15 Sep 2023 2 repositories listed Syntology ran 6 of 10 samples · 4 unverified
  Molecular Representation Learning (MRL) has emerged as a powerful tool for drug and materials discovery in a variety of tasks such as virtual screening and inverse design.
• MUBen: Benchmarking the Uncertainty of Molecular Representation Models
  14 Jun 2023 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  While some studies have included UQ to improve molecular pre-trained models, the process of selecting suitable backbone and UQ methods for reliable molecular uncertainty estimation remains underexplored.
• Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction
  24 Apr 2023 2 repositories listed
  Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery.
• A Systematic Survey of Chemical Pre-trained Models
  29 Oct 2022 2 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Deep learning has achieved remarkable success in learning representations for molecules, which is crucial for various biochemical applications, ranging from property prediction to drug design.
• Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching
  27 Jun 2022 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Further by leveraging an SE(3)-invariant score matching method, we propose GeoSSL-DDM in which the coordinate denoising proxy task is effectively boiled down to denoising the pairwise atomic distances in a molecule.
• SSI–DDI: Substructure–Substructure Interactions for Drug–Drug Interaction Prediction
  7 Nov 2021 2 repositories listed
  A major concern with co-administration of different drugs is the high risk of interference between their mechanisms of action, known as adverse drug–drug interactions (DDIs), which can cause serious injuries to the…
• Multiresolution Equivariant Graph Variational Autoencoder
  2 Jun 2021 2 repositories listed Syntology ran 7 of 14 samples · 7 unverified · 6 pointer-only (licence)
  In this paper, we propose Multiresolution Equivariant Graph Variational Autoencoders (MGVAE), the first hierarchical generative model to learn and generate graphs in a multiresolution and equivariant manner.
• Molecular representation learning with language models and domain-relevant auxiliary tasks
  26 Nov 2020 2 repositories listed
  We apply a Transformer architecture, specifically BERT, to learn flexible and high quality molecular representations for drug discovery problems.
• Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation
  31 May 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  SELFIES can be directly applied in arbitrary machine learning models without the adaptation of the models; each of the generated molecule candidates is valid.
• Learning Continuous and Data-Driven Molecular Descriptors by Translating Equivalent Chemical Representations
  19 Nov 2018 2 repositories listed
  In this work, we propose to exploit the powerful ability of deep neural networks to learn a feature representation from low-level encodings of a huge corpus of chemical structures.
• Molecular Machine Learning Using Euler Characteristic Transforms
  4 Jul 2025 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  More importantly, its combination with traditional representations, particularly with the AVALON fingerprint, significantly \emph{enhances predictive performance}, outperforming other methods on most datasets.
• 2DNMRGym: An Annotated Experimental Dataset for Atom-Level Molecular Representation Learning in 2D NMR via Surrogate Supervision
  16 May 2025 1 repository listed
  In this work, we introduce 2DNMRGym, the first annotated experimental dataset designed for ML-based molecular representation learning in 2D NMR.
• MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
  22 Feb 2025 1 repository listed Syntology ran 6 of 12 samples · 6 unverified · 12 pointer-only (licence)
  In this paper, we propose to utilize the energy spectra to enhance the pre-training of 3D molecular representations (MolSpectra), thereby infusing the knowledge of quantum mechanics into the molecular representations.
• UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
  18 Feb 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Drug discovery is crucial for identifying candidate drugs for various diseases.
• GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation
  14 Jan 2025 1 repository listed Syntology ran 1 of 6 samples · 5 unverified
  Typically, the retrosynthesis prediction involves two phases: Reaction Center Identification and Reactant Generation.
• MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
  21 Dec 2024 1 repository listed Syntology ran 2 of 4 samples · 2 unverified
  Molecular representation learning plays a crucial role in various downstream tasks, such as molecular property prediction and drug design.
• BAPULM: Binding Affinity Prediction using Language Models
  6 Nov 2024 1 repository listed
  Identifying drug-target interactions is essential for developing effective therapeutics.
• Chemical Language Model Linker: blending text and molecules with modular adapters
  26 Oct 2024 1 repository listed
  The development of large language models and multi-modal models has enabled the appealing idea of generating novel molecules from text descriptions.
• Multi-view biomedical foundation models for molecule-target and property prediction
  25 Oct 2024 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  We show that the multi-view models perform robustly and are able to balance the strengths and weaknesses of specific views.
• MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
  10 Oct 2024 1 repository listed Syntology ran 5 of 6 samples · 1 unverified
  In this work, we propose a simple transformer-based baseline for multimodal molecular representation learning, integrating three distinct modalities: SMILES strings, 2D graph representations, and 3D conformers of…
• Molecular Graph Representation Learning via Structural Similarity Information
  13 Sep 2024 1 repository listed
  In particular, we propose a specially designed graph that leverages graph kernel algorithms to represent the similarity between molecules quantitatively.
• Active Learning of Molecular Data for Task-Specific Objectives
  20 Aug 2024 1 repository listed
  We established that the performance of AL depends on the relative distribution of the target molecules in comparison to the total dataset distribution, with the largest computational savings achieved when their overlap…
• GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
  24 Jun 2024 1 repository listed
  We argue that there is a strong need for a general and flexible framework for learning both invariant and equivariant features.
• Learning Molecular Representation in a Cell
  17 Jun 2024 1 repository listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  A sufficiency objective decodes the representation to align with different feature spaces from the molecule's neighborhood in the context graph.

Syntology lines on 17 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.