{"total":34,"rows":[{"id":"2310.18278","title":"Navigating protein landscapes with a machine-learned transferable coarse-grained model","created":"2023-10-27","cited_by_count":23,"area":null},{"id":"2410.09667","title":"EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants","created":"2024-10-12","cited_by_count":16,"area":null},{"id":"2402.17660","title":"TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations","created":"2024-02-27","cited_by_count":15,"area":null},{"id":"2510.07589","title":"Transferable Generative Models Bridge Femtosecond to Nanosecond Time-Step Molecular Dynamics","created":"2025-10-08","cited_by_count":11,"area":null},{"id":"2302.07071","title":"Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics","created":"2023-02-14","cited_by_count":9,"area":null},{"id":"2402.13984","title":"Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators","created":"2024-02-21","cited_by_count":8,"area":null},{"id":"2509.13294","title":"Accelerating Protein Molecular Dynamics Simulation with DeepJump","created":"2025-09-16","cited_by_count":6,"area":null},{"id":"2509.24779","title":"MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models","created":"2025-09-29","cited_by_count":6,"area":null},{"id":"2402.01195","title":"Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations","created":"2024-02-02","cited_by_count":5,"area":null},{"id":"2302.03786","title":"Analyzing the Performance of Deep Encoder-Decoder Networks as Surrogates for a Diffusion Equation","created":"2023-02-07","cited_by_count":4,"area":null},{"id":"2306.11375","title":"Top-down machine learning of coarse-grained protein force-fields","created":"2023-06-20","cited_by_count":4,"area":null},{"id":"2409.03118","title":"Generative artificial intelligence for computational chemistry: a roadmap to predicting emergent phenomena","created":"2024-09-04","cited_by_count":3,"area":null},{"id":"2409.17852","title":"AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics","created":"2024-09-26","cited_by_count":3,"area":null},{"id":"2510.11148","title":"Enhanced Sampling for Efficient Learning of Coarse-Grained Machine Learning Potentials","created":"2025-10-13","cited_by_count":3,"area":null},{"id":"2604.01169","title":"Bridging the Simulation-to-Experiment Gap with Generative Models using Adversarial Distribution Alignment","created":"2026-04-01","cited_by_count":2,"area":null},{"id":"2503.19186","title":"Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification","created":"2025-03-24","cited_by_count":1,"area":null},{"id":"2509.14600","title":"TICA-Based Free Energy Matching for Machine-Learned Molecular Dynamics","created":"2025-09-18","cited_by_count":1,"area":null},{"id":"2509.17224","title":"AI-based Methods for Simulating, Sampling, and Predicting Protein Ensembles","created":"2025-09-21","cited_by_count":1,"area":null},{"id":"2510.17187","title":"A Standardized Benchmark for Machine-Learned Molecular Dynamics using Weighted Ensemble Sampling","created":"2025-10-20","cited_by_count":1,"area":null},{"id":"2604.25244","title":"Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics","created":"2026-04-28","cited_by_count":1,"area":null},{"id":"2607.29158","title":"Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2312.03404","title":"A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks","created":"2023-12-06","cited_by_count":0,"area":null},{"id":"2410.02847","title":"Deep Signature: Characterization of Large-Scale Molecular Dynamics","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2411.19629","title":"OpenQDC: Open Quantum Data Commons","created":"2024-11-29","cited_by_count":0,"area":null},{"id":"2502.00798","title":"Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors","created":"2025-02-02","cited_by_count":0,"area":null},{"id":"2502.16828","title":"Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning","created":"2025-02-24","cited_by_count":0,"area":null},{"id":"2504.01973","title":"Universally applicable and tunable graph-based coarse-graining for Machine learning force fields","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2506.19628","title":"Operator Forces For Coarse-Grained Molecular Dynamics","created":"2025-06-24","cited_by_count":0,"area":null},{"id":"2602.10637","title":"Coarse-Grained Boltzmann Generators","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2602.13140","title":"FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2605.12823","title":"Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2606.14111","title":"Temperature transferable Machine Learned Coarse Grained model for proteins","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2606.14737","title":"Learning Topological Representations of Protein Structure and Dynamics","created":"2026-06-02","cited_by_count":0,"area":null},{"id":"2607.10887","title":"Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy","created":"2026-07-12","cited_by_count":0,"area":null}],"next_cursor":null}