{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/drug-discovery/papers/11","list_of":"/task/drug-discovery","task":"Drug Discovery","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":11,"pages_in_order":14,"rows_per_page":100,"rows":[1001,1100],"of":1337,"counts":{"archive_papers_tagged":1337,"with_a_code_link":566,"where_syntology_ran_a_sample":182,"not_listed_spam_title":0,"listed":1337,"listed_where_code_ran":182,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":146,"every_run_a_failure_of_syntologys_instrument":36,"listed_with_a_run_with_no_instrument_failure":146,"listed_every_run_a_failure_of_syntologys_instrument":36,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/drug-discovery","prev":"/task/drug-discovery/papers/10","next":"/task/drug-discovery/papers/12","papers":[{"url":null,"slug":"predicting-molecule-target-interaction-by","title":"Predicting Molecule-Target Interaction by Learning Biomedical Network and Molecule Representations","date":"2023-02-02","arxiv_id":"2302.00981","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-for-biomedical-causal","title":"Large Language Models for Biomedical Knowledge Graph Construction: Information extraction from EMR notes","date":"2023-01-29","arxiv_id":"2301.12473","repositories_listed":0,"syntology":null},{"url":null,"slug":"everything-is-connected-graph-neural-networks","title":"Everything is Connected: Graph Neural Networks","date":"2023-01-19","arxiv_id":"2301.08210","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-classical-convolutional-neural-1","title":"Hybrid quantum-classical convolutional neural networks to improve molecular protein binding affinity predictions","date":"2023-01-16","arxiv_id":"2301.06331","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-organoid-image-analysis-platforms","title":"A survey on Organoid Image Analysis Platforms","date":"2023-01-06","arxiv_id":"2301.02341","repositories_listed":0,"syntology":null},{"url":null,"slug":"protein-ligand-complex-generator-drug","title":"Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform","date":"2023-01-03","arxiv_id":"2301.00984","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthesis-driven-design-of-3d-molecules-for","title":"Synthesis-driven design of 3D molecules for structure-based drug discovery using geometric transformers","date":"2022-12-31","arxiv_id":"2301.00167","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-based-drug-discovery-with-deep","title":"Structure-based drug discovery with deep learning","date":"2022-12-26","arxiv_id":"2212.13295","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-how-ai-needs-to-change-to-advance-the","title":"On How AI Needs to Change to Advance the Science of Drug Discovery","date":"2022-12-23","arxiv_id":"2212.12560","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphix-graph-based-in-silico-xai-explainable","title":"GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network","date":"2022-12-21","arxiv_id":"2212.10788","repositories_listed":0,"syntology":null},{"url":null,"slug":"economic-impacts-of-ai-augmented-r-d","title":"Economic impacts of AI-augmented R&D","date":"2022-12-15","arxiv_id":"2212.08198","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-quantum-generative-adversarial","title":"Hybrid Quantum Generative Adversarial Networks for Molecular Simulation and Drug Discovery","date":"2022-12-15","arxiv_id":"2212.07826","repositories_listed":0,"syntology":null},{"url":null,"slug":"molecular-graph-generation-by-decomposition","title":"Molecular Graph Generation by Decomposition and Reassembling","date":"2022-12-11","arxiv_id":"2302.00587","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-role-of-ai-in-drug-discovery-challenges","title":"The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies","date":"2022-12-08","arxiv_id":"2212.08104","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-molecule-properties-through-2-stage","title":"Improving Molecule Properties Through 2-Stage VAE","date":"2022-12-06","arxiv_id":"2212.02750","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-scoring-functions-for-drug","title":"Machine Learning Scoring Functions for Drug Discoveries from Experimental and Computer-Generated Protein-Ligand Structures: Towards Per-Target Scoring Functions","date":"2022-12-06","arxiv_id":"2212.03202","repositories_listed":0,"syntology":null},{"url":null,"slug":"energy-based-generative-models-for-target","title":"Energy-based Generative Models for Target-specific Drug Discovery","date":"2022-12-05","arxiv_id":"2212.02404","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-approach-to-the-prediction-of","title":"A Deep Learning Approach to the Prediction of Drug Side-Effects on Molecular Graphs","date":"2022-11-30","arxiv_id":"2211.16871","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-drug-repurposing-candidates-and","title":"KGML-xDTD: A Knowledge Graph-based Machine Learning Framework for Drug Treatment Prediction and Mechanism Description","date":"2022-11-30","arxiv_id":"2212.01384","repositories_listed":0,"syntology":null},{"url":null,"slug":"molecular-joint-representation-learning-via","title":"Molecular Joint Representation Learning via Multi-modal Information","date":"2022-11-25","arxiv_id":"2211.14042","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-quantum-algorithms-for-chemical","title":"Variational Quantum Algorithms for Chemical Simulation and Drug Discovery","date":"2022-11-15","arxiv_id":"2211.07854","repositories_listed":0,"syntology":null},{"url":null,"slug":"drug-target-affinity-prediction-method-based","title":"Drug-target affinity prediction method based on consistent expression of heterogeneous data","date":"2022-11-13","arxiv_id":"2211.06792","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-graph-neural-networks-and","title":"Application of Graph Neural Networks and graph descriptors for graph classification","date":"2022-11-07","arxiv_id":"2211.03666","repositories_listed":0,"syntology":null},{"url":null,"slug":"todd-topological-compound-fingerprinting-in","title":"ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery","date":"2022-11-07","arxiv_id":"2211.03808","repositories_listed":0,"syntology":null},{"url":null,"slug":"recent-developments-in-structure-based","title":"Recent Developments in Structure-Based Virtual Screening Approaches","date":"2022-11-06","arxiv_id":"2211.03208","repositories_listed":0,"syntology":null},{"url":null,"slug":"mole-a-molecular-foundation-model-for-drug","title":"MolE: a molecular foundation model for drug discovery","date":"2022-11-03","arxiv_id":"2211.02657","repositories_listed":0,"syntology":null},{"url":null,"slug":"ccs-explorer-relevance-prediction-extractive","title":"CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies","date":"2022-11-01","arxiv_id":"2211.00201","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-point-prediction-uncertainties-in","title":"Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery","date":"2022-10-31","arxiv_id":"2210.17043","repositories_listed":0,"syntology":null},{"url":null,"slug":"drug-repositioning-for-alzheimer-s-disease","title":"Drug repositioning for Alzheimer's disease with transfer learning","date":"2022-10-27","arxiv_id":"2210.15271","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpreting-chemical-words-of-a-data-driven","title":"Exploring Data-Driven Chemical SMILES Tokenization Approaches to Identify Key Protein-Ligand Binding Moieties","date":"2022-10-26","arxiv_id":"2210.14642","repositories_listed":0,"syntology":null},{"url":null,"slug":"faster-and-more-diverse-de-novo-molecular","title":"Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES","date":"2022-10-22","arxiv_id":"2210.12458","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodology-for-the-prediction-of-drug","title":"A Methodology for the Prediction of Drug Target Interaction using CDK Descriptors","date":"2022-10-20","arxiv_id":"2210.11482","repositories_listed":0,"syntology":null},{"url":null,"slug":"multibody-molecular-docking-on-a-quantum","title":"Multibody molecular docking on a quantum annealer","date":"2022-10-20","arxiv_id":"2210.11401","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-based-drug-design-with-geometric","title":"Structure-based drug design with geometric deep learning","date":"2022-10-19","arxiv_id":"2210.11250","repositories_listed":0,"syntology":null},{"url":null,"slug":"pemp-leveraging-physics-properties-to-enhance","title":"PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction","date":"2022-10-18","arxiv_id":"2211.01978","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-transformer-based-generative-model-for-de","title":"A Transformer-based Generative Model for De Novo Molecular Design","date":"2022-10-17","arxiv_id":"2210.08749","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-neural-processes-for-molecules","title":"Conditional Neural Processes for Molecules","date":"2022-10-17","arxiv_id":"2210.09211","repositories_listed":0,"syntology":null},{"url":null,"slug":"industry-scale-orchestrated-federated","title":"Industry-Scale Orchestrated Federated Learning for Drug Discovery","date":"2022-10-17","arxiv_id":"2210.08871","repositories_listed":0,"syntology":null},{"url":null,"slug":"substructure-atom-cross-attention-for","title":"Substructure-Atom Cross Attention for Molecular Representation Learning","date":"2022-10-15","arxiv_id":"2210.08243","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-lipid-droplet-microarray-fabrication","title":"Scalable lipid droplet microarray fabrication, validation, and screening","date":"2022-10-13","arxiv_id":"2210.07377","repositories_listed":0,"syntology":null},{"url":null,"slug":"e3bind-an-end-to-end-equivariant-network-for","title":"E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking","date":"2022-10-12","arxiv_id":"2210.06069","repositories_listed":0,"syntology":null},{"url":null,"slug":"modular-flows-differential-molecular","title":"Modular Flows: Differential Molecular Generation","date":"2022-10-12","arxiv_id":"2210.06032","repositories_listed":0,"syntology":null},{"url":null,"slug":"antibody-representation-learning-for-drug","title":"Antibody Representation Learning for Drug Discovery","date":"2022-10-05","arxiv_id":"2210.02881","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-reliable-and-interpretable","title":"Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning","date":"2022-09-29","arxiv_id":"2210.07145","repositories_listed":0,"syntology":null},{"url":null,"slug":"causal-inference-in-drug-discovery-and","title":"Causal inference in drug discovery and development","date":"2022-09-29","arxiv_id":"2209.14664","repositories_listed":0,"syntology":null},{"url":"/paper/mars-a-motif-based-autoregressive-model-for","slug":"mars-a-motif-based-autoregressive-model-for","title":"MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction","date":"2022-09-27","arxiv_id":"2209.13178","repositories_listed":0,"syntology":null},{"url":null,"slug":"vddb-a-comprehensive-resource-and-machine","title":"VDDB: a comprehensive resource and machine learning platform for antiviral drug discovery","date":"2022-09-17","arxiv_id":"2209.13521","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-pre-trained-models-really-learn-better","title":"Can Pre-trained Models Really Learn Better Molecular Representations for AI-aided Drug Discovery?","date":"2022-08-21","arxiv_id":"2209.07423","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-biologically-inspired-evaluation-of","title":"A biologically-inspired multi-modal evaluation of molecular generative machine learning","date":"2022-08-20","arxiv_id":"2208.09658","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-small-molecule-generation-using","title":"Improving Small Molecule Generation using Mutual Information Machine","date":"2022-08-18","arxiv_id":"2208.09016","repositories_listed":0,"syntology":null},{"url":null,"slug":"widely-used-and-fast-de-novo-drug-design-by-a","title":"Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model","date":"2022-08-14","arxiv_id":"2209.07405","repositories_listed":0,"syntology":null},{"url":null,"slug":"cloud-based-real-time-molecular-screening","title":"Cloud-Based Real-Time Molecular Screening Platform with MolFormer","date":"2022-08-13","arxiv_id":"2208.06665","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-the-gap-between-target-based-and","title":"Bridging the gap between target-based and cell-based drug discovery with a graph generative multi-task model","date":"2022-08-09","arxiv_id":"2208.04944","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-of-semi-supervised-learning","title":"Comparison of semi-supervised learning methods for High Content Screening quality control","date":"2022-08-09","arxiv_id":"2208.04592","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-optimal-likelihood-free-method-for","title":"An Optimal Likelihood Free Method for Biological Model Selection","date":"2022-08-03","arxiv_id":"2208.02344","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-networks-for-the-prediction-of-1","title":"Graph neural networks for the prediction of molecular structure-property relationships","date":"2022-07-25","arxiv_id":"2208.04852","repositories_listed":0,"syntology":null},{"url":null,"slug":"ribbon-cost-effective-and-qos-aware-deep","title":"RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances","date":"2022-07-23","arxiv_id":"2207.11434","repositories_listed":0,"syntology":null},{"url":null,"slug":"does-gnn-pretraining-help-molecular","title":"Does GNN Pretraining Help Molecular Representation?","date":"2022-07-13","arxiv_id":"2207.06010","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-network-bandits","title":"Graph Neural Network Bandits","date":"2022-07-13","arxiv_id":"2207.06456","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-scale-sinusoidal-embeddings-enable","title":"Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data","date":"2022-07-06","arxiv_id":"2207.02980","repositories_listed":0,"syntology":null},{"url":null,"slug":"pre-training-transformers-for-molecular","title":"Pre-training Transformers for Molecular Property Prediction Using Reaction Prediction","date":"2022-07-06","arxiv_id":"2207.02724","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimally-weighted-ensembles-of-regression","title":"Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications","date":"2022-06-22","arxiv_id":"2206.11263","repositories_listed":0,"syntology":null},{"url":"/paper/0-1-deep-neural-networks-via-block-coordinate","slug":"0-1-deep-neural-networks-via-block-coordinate","title":"0/1 Deep Neural Networks via Block Coordinate Descent","date":"2022-06-19","arxiv_id":"2206.09379","repositories_listed":0,"syntology":null},{"url":null,"slug":"direct-generation-of-protein-conformational","title":"Direct Generation of Protein Conformational Ensembles via Machine Learning","date":"2022-06-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-learning-for-label-sparsity","title":"Self-supervised Learning for Label Sparsity in Computational Drug Repositioning","date":"2022-06-01","arxiv_id":"2206.00262","repositories_listed":0,"syntology":null},{"url":null,"slug":"coin-co-cluster-infomax-for-bipartite-graphs","title":"COIN: Co-Cluster Infomax for Bipartite Graphs","date":"2022-05-31","arxiv_id":"2206.00006","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-learning-for-discovery","title":"Adaptive Sampling for Discovery","date":"2022-05-30","arxiv_id":"2205.14829","repositories_listed":0,"syntology":null},{"url":null,"slug":"surrogate-modeling-for-bayesian-optimization","title":"Surrogate modeling for Bayesian optimization beyond a single Gaussian process","date":"2022-05-27","arxiv_id":"2205.14090","repositories_listed":0,"syntology":null},{"url":null,"slug":"tyger-task-type-generic-active-learning-for","title":"Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction","date":"2022-05-23","arxiv_id":"2205.11279","repositories_listed":0,"syntology":null},{"url":null,"slug":"de-novo-design-of-protein-target-specific-1","title":"De novo design of protein target specific scaffold-based Inhibitors via Reinforcement Learning","date":"2022-05-21","arxiv_id":"2205.10473","repositories_listed":0,"syntology":null},{"url":null,"slug":"helixadmet-a-robust-and-endpoint-extensible","title":"HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer","date":"2022-05-17","arxiv_id":"2205.08055","repositories_listed":0,"syntology":null},{"url":null,"slug":"pronet-db-a-proteome-wise-database-for","title":"ProNet DB: A proteome-wise database for protein surface property representations and RNA-binding profiles","date":"2022-05-16","arxiv_id":"2205.07673","repositories_listed":0,"syntology":null},{"url":null,"slug":"trustworthy-graph-neural-networks-aspects","title":"Trustworthy Graph Neural Networks: Aspects, Methods and Trends","date":"2022-05-16","arxiv_id":"2205.07424","repositories_listed":0,"syntology":null},{"url":"/paper/high-performance-of-gradient-boosting-in","slug":"high-performance-of-gradient-boosting-in","title":"High Performance of Gradient Boosting in Binding Affinity Prediction","date":"2022-05-14","arxiv_id":"2205.07023","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaborative-drug-discovery-inference-level","title":"Collaborative Drug Discovery: Inference-level Data Protection Perspective","date":"2022-05-13","arxiv_id":"2205.06506","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-b-vae-for-de-novo-molecular","title":"Conditional β-VAE for De Novo Molecular Generation","date":"2022-05-02","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-b-vae-for-de-novo-molecular-1","title":"Conditional $β$-VAE for De Novo Molecular Generation","date":"2022-05-01","arxiv_id":"2205.01592","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-pride-without-2d-prejudice-bias-controlled","title":"3D pride without 2D prejudice: Bias-controlled multi-level generative models for structure-based ligand design","date":"2022-04-22","arxiv_id":"2204.10663","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-score-based-geometric-model-for-molecular","title":"DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations","date":"2022-04-19","arxiv_id":"2204.08672","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-trustworthy-graph","title":"A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability","date":"2022-04-18","arxiv_id":"2204.08570","repositories_listed":0,"syntology":null},{"url":null,"slug":"drflm-distributionally-robust-federated","title":"DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup","date":"2022-04-16","arxiv_id":"2204.07742","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-machine-learning-framework-for","title":"Quantum Machine Learning Framework for Virtual Screening in Drug Discovery: a Prospective Quantum Advantage","date":"2022-04-08","arxiv_id":"2204.04017","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-pocket-3d-graphs-enhance-ligand-target","title":"In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation","date":"2022-04-05","arxiv_id":"2204.02513","repositories_listed":0,"syntology":null},{"url":null,"slug":"molgensurvey-a-systematic-survey-in-machine","title":"MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design","date":"2022-03-28","arxiv_id":"2203.14500","repositories_listed":0,"syntology":null},{"url":null,"slug":"meaningful-machine-learning-models-and","title":"Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns","date":"2022-03-25","arxiv_id":"2204.06348","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-equilibrium-molecular-geometries-in-graph","title":"Non-equilibrium molecular geometries in graph neural networks","date":"2022-03-07","arxiv_id":"2203.04697","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-photonic-chip-based-machine-learning","title":"A photonic chip-based machine learning approach for the prediction of molecular properties","date":"2022-03-03","arxiv_id":"2203.02285","repositories_listed":0,"syntology":null},{"url":null,"slug":"candidatedrug4cancer-an-open-molecular-graph","title":"CandidateDrug4Cancer: An Open Molecular Graph Learning Benchmark on Drug Discovery for Cancer","date":"2022-03-02","arxiv_id":"2203.00836","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-molecular-graph-generation-via","title":"Interpretable Molecular Graph Generation via Monotonic Constraints","date":"2022-02-28","arxiv_id":"2203.00412","repositories_listed":0,"syntology":null},{"url":null,"slug":"equivariant-graph-attention-networks-for","title":"Equivariant Graph Attention Networks for Molecular Property Prediction","date":"2022-02-20","arxiv_id":"2202.09891","repositories_listed":0,"syntology":null},{"url":null,"slug":"modular-multi-source-prediction-of-drug-side","title":"Modular multi-source prediction of drug side-effects with DruGNN","date":"2022-02-15","arxiv_id":"2202.08147","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-discover-medicines","title":"Learning to Discover Medicines","date":"2022-02-14","arxiv_id":"2202.07096","repositories_listed":0,"syntology":null},{"url":null,"slug":"novel-prediction-methods-for-virtual-drug","title":"Novel prediction methods for virtual drug screening","date":"2022-02-14","arxiv_id":"2202.06635","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-architecture-search-for-brain","title":"Automated Architecture Search for Brain-inspired Hyperdimensional Computing","date":"2022-02-11","arxiv_id":"2202.05827","repositories_listed":0,"syntology":null},{"url":null,"slug":"target-aware-molecular-graph-generation","title":"Target-aware Molecular Graph Generation","date":"2022-02-10","arxiv_id":"2202.04829","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactivity-the-missing-link-between","title":"Interactivity: the missing link between virtual reality technology and drug discovery pipelines","date":"2022-02-08","arxiv_id":"2202.03953","repositories_listed":0,"syntology":null},{"url":null,"slug":"nonmyopic-multiclass-active-search-for","title":"Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery","date":"2022-02-08","arxiv_id":"2202.03593","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-fragment-based-3d-molecular-design","title":"Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning","date":"2022-02-01","arxiv_id":"2202.00658","repositories_listed":0,"syntology":null},{"url":null,"slug":"sugar-efficient-subgraph-level-training-via","title":"SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning","date":"2022-01-31","arxiv_id":"2202.00075","repositories_listed":0,"syntology":null},{"url":null,"slug":"alphafold-accelerates-artificial-intelligence","title":"AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor","date":"2022-01-21","arxiv_id":"2201.09647","repositories_listed":0,"syntology":null}],"record_sha256":"0f14c539fe6ef5af4199e57c484d36c4842e0a1e9bb09c5b118d30083176589d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}