Quantum chemistry structures and properties of 134 kilo molecules

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Items 901–1,000 of 1,001

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31. GrapheNet: a deep learning framework for predicting the physical and electronic properties of nanographenes using images
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34. Uni‐Electrolyte: An Artificial Intelligence Platform for Designing Electrolyte Molecules for Rechargeable Batteries
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35. Machine Learning Transition State Geometries and Applications in Reaction Property Prediction
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39. Troubleshooting unstable molecules in chemical space
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41. Molecular Screening for Terahertz Detection with Machine-Learning-Based Methods
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42. Seeking the Optimal Descriptor for S N 2 Reactions through Statistical Analysis of Density Functional Theory Results
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43. Breaking the Expression Bottleneck of Graph Neural Networks
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44. Metric learning for kernel ridge regression: assessment of molecular similarity
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46. Can AI Help Improve Water Quality? Towards the Prediction of Degradation of Micropollutants in Wastewater.
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47. Multiresolution graph transformers and wavelet positional encoding for learning long-range and hierarchical structures
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48. Low-Data Deep Quantum Chemical Learning for Accurate MP2 and Coupled-Cluster Correlations
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49. Fusion of Multiple Spectra for Investigating Chemical Bonding Properties via Machine Learning
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50. Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE
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53. Resilience of Hund's rule in the chemical space of small organic molecules
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54. Modeling Zinc Complexes Using Neural Networks
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55. Molecular Graph Generation with Deep Reinforced Multitask Network and Adversarial Imitation Learning
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56. Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks
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57. Machine Learning and Big-Data in Computational Chemistry
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58. Physical machine learning outperforms "human learning" in Quantum Chemistry
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59. Gated Graph Recursive Neural Networks for Molecular Property Prediction
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60. Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces
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61. Very Deep Graph Neural Networks Via Noise Regularisation.
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62. High-Throughput Screening of Promising Redox-Active Molecules with MolGAT
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70. RGCVAE: relational graph conditioned variational autoencoder for molecule design
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77. Standards-based curation of a decade-old digital repository dataset of molecular information
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79. Machine Learning and Big-Data in Computational Chemistry
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89. What's Left for a Computational Chemist To Do in the Age of Machine Learning?
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92. Molecule Property Prediction and Classification with Graph Hypernetworks
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98. Multitask methods for predicting molecular properties from heterogeneous data
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99. Zero shot molecular generation via similarity kernels
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