Inc2

Published datasets resulting from project Incubator 2 "Active Machine Learning for Computational Materials Design".

10.24435/materialscloud:9p-8a — Fixed node diffusion Monte Carlo energies for over one thousand small organic molecules, by B. Huang, A. von Lilienfeld, J. Krogel, A. Benali
Related MARVEL publication:
- B. Huang, O. A. von Lilienfeld, J. T. Krogel, A. Benali, Toward DMC Accuracy Across Chemical Space with Scalable Δ-QML, Journal of Chemical Theory and Computation 19, 1711–1721 (2023). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2

10.5281/zenodo.5606918 — Alchemical CPHF perturbator, by G. Domenichini
Related MARVEL publication:
- G. Domenichini, O. A. von Lilienfeld, Alchemical geometry relaxation, The Journal of Chemical Physics 156, 184801 (2022). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.6823150 — Supplementary Information of Geometry Relaxation and Transition State Search with Quantum Machine Learning, by S. Heinen, G. F. Von Rudorff, O. A. Von Lilienfeld
Related MARVEL publication:
- S. Heinen, G. F. von Rudorff, O. A. von Lilienfeld, Transition state search and geometry relaxation throughout chemical compound space with quantum machine learning, The Journal of Chemical Physics 157, 221102 (2022). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.6401711 — Data and Code: Ab initio machine learning of phase space averages, by J. Weinreich, D. Lemm, G. Von Rudorff, A. Von Lilienfeld
Related MARVEL publication:
- J. Weinreich, D. Lemm, G. F. von Rudorff, O. A. von Lilienfeld, Ab initio machine learning of phase space averages, The Journal of Chemical Physics 157, 024303 (2022). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2

10.24435/materialscloud:hj-xe — Maximum volume simplex method for automatic selection and classification of atomic environments and environment descriptor compression, by B. Parsaeifard, D. Tomerini, D. S. De, S. Goedecker
Related MARVEL publication:
- B. Parsaeifard, D. S. De, A. S. Christensen, F. A. Faber, E. Kocer, S. De, J. Behler, O. A. von Lilienfeld, S. Goedecker, An assessment of the structural resolution of various fingerprints commonly used in machine learning, Machine Learning: Science and Technology 2, 015018 (2021). [Open Access URL]
  Group(s): Goedecker, von Lilienfeld / Project(s): DD1, INC2
10.24435/materialscloud:g6-ft — 3DMolNet: a generative network for molecular structures, by V. Nesterov, M. Wieser, V. Roth
Related MARVEL publication:
- V. Nesterov, M. Wieser, V. Roth, 3DMolNet: A Generative Network for Molecular Structures, arXiv:2010.06477 (2020). [Open Access URL]
  Group(s): Roth / Project(s): INC2
10.24435/materialscloud:yg-r0 — Effects of perturbation order and basis set on alchemical predictions within 14 electron diatomic molecules series, detailed analysis of the various sources of errors, by G. Domenichini, G. F. Von Rudorff, O. A. Von Lilienfeld
Related MARVEL publication:
- G. Domenichini, G. F. von Rudorff, O. A. von Lilienfeld, Effects of perturbation order and basis set on alchemical predictions, The Journal of Chemical Physics 153, 144118 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.24435/materialscloud:1s-51 — Dictionary of 140k GDB and ZINC derived AMONs, by B. Huang, A. Von Lilienfeld
Related MARVEL publication:
- B. Huang, O. A. von lilienfeld, Dictionary of 140k GDB and ZINC derived AMONs, arXiv:2008.05260 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.4925938 — Towards the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space, by S. Heinen, G. F. Von Rudorff, A. Von Lilienfeld
Related MARVEL publication:
- S. Heinen, G. F. von Rudorff, O. A. von Lilienfeld, Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space, The Journal of Chemical Physics 155, 064105 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.4432606 — Elucidating atmospheric brown carbon - Supplanting chemical intuition with exhaustive enumeration and machine learning, by E. Tapavicza, G. F. von Rudorff, D. O. De Haan, M. Contin, C. George, M. Riva, O. A. von Lilienfeld
Related MARVEL publication:
- E. Tapavicza, G. F. von Rudorff, D. O. D. Haan, M. Contin, C. George, M. Riva, O. A. von Lilienfeld, Elucidating an Atmospheric Brown Carbon Species—Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning, Environmental Science & Technology 55, 8447–8457 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.3994178 — Solving the inverse materials design problem with alchemical chirality, by G. F. V. Rudorff, O. A. V. Lilienfeld
Related MARVEL publication:
- G. F. von Rudorff, O. A. von Lilienfeld, Simplifying inverse materials design problems for fixed lattices with alchemical chirality, Science Advances 7, eabf1173 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.6084/m9.figshare.c.978904.v5 — Quantum chemistry structures and properties of 134 kilo molecules, by R. Ramakrishnan, P. Dral, M. Rupp, O. A. V. Lilienfeld
Related MARVEL publication:
- D. Lemm, G. F. von Rudorff, O. A. von Lilienfeld, Machine learning based energy-free structure predictions of molecules, transition states, and solids, Nature Communications 12, 4468 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
github.com/bmda-unibas/CondInvarianceCC — Learning Conditional Invariance through Cycle Consistency, by M. Samarin
Related MARVEL publication:
- M. Samarin, V. Nesterov, M. Wieser, A. Wieczorek, S. Parbhoo, and V. Roth, Learning Conditional Invariance through Cycle Consistency, in 43rd German Conference on Pattern Recognition (GCPR 2021), Lecture Notes in Computer Science (C. Bauckhage, J. Gall, and A. Schwing, eds., Springer International Publishing, Cham, 2021). [Open Access URL]
  Group(s): Roth / Project(s): INC2
10.24435/materialscloud:wy-kn — Revised MD17 dataset, by A. Christensen, O. A. Von Lilienfeld
Related MARVEL publication:
- A. S. Christensen, O. A. von lilienfeld, On the role of gradients for machine learning of molecular energies and forces, Machine Learning: Science and Technology 1, 045018 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.24435/materialscloud:sf-tz — QMrxn20: Thousands of reactants and transition states for competing E2 and S_N2 reactions, by G. F. Von Rudorff, S. N. Heinen, M. Bragato, O. A. Von Lilienfeld
Related MARVEL publications:
- D. Lemm, G. F. von Rudorff, O. A. von Lilienfeld, Machine learning based energy-free structure predictions of molecules, transition states, and solids, Nature Communications 12, 4468 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
- G. F. von Rudorff, S. N. Heinen, M. Bragato, O. A. von lilienfeld, Thousands of reactants and transition states for competing E2 and S_N2 reactions, Machine Learning: Science and Technology 1, 045026 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.24435/materialscloud:2020.0051/v1 — The QMspin data set: Several thousand carbene singlet and triplet state structures and vertical spin gaps computed at MRCISD+Q-F12/cc-pVDZ-F12 level of theory, by M. Schwilk, D. N. Tahchieva, O. A. Von Lilienfeld
Related MARVEL publications:
- D. Lemm, G. F. von Rudorff, O. A. von Lilienfeld, Machine learning based energy-free structure predictions of molecules, transition states, and solids, Nature Communications 12, 4468 (2021). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
- M. Schwilk, D. N. Tahchieva, O. A. von lilienfeld, Large yet bounded: Spin gap ranges in carbenes, arXiv:2004.10600 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.817332 — Qmlcode/Qml: Release V0.3.1, by A. S. Christensen, F. A. Faber, B. Huang, L. A. Bratholm, A. Tkatchenko, K. Müller, O. A. V. Lilienfeld
Related MARVEL publication:
- A. S. Christensen, L. A. Bratholm, F. A. Faber, O. A. von Lilienfeld, FCHL revisited: Faster and more accurate quantum machine learning, The Journal of Chemical Physics 152, 044107 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.3952671 — chemspacelab/Enhanced-Hammett: Enhanced_Hammett, by MarcoBrag
Related MARVEL publication:
- M. Bragato, G. F. von Rudorff, O. A. von Lilienfeld, Data enhanced Hammett-equation: reaction barriers in chemical space, Chemical Science 11, 11859–11868 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.3923823 — H₂CO Dataset, by S. Käser, D. Koner, A. S. Christensen, O. A. von Lilienfeld, M. Meuwly
Related MARVEL publication:
- S. Käser, D. Koner, A. S. Christensen, O. A. von lilienfeld, M. Meuwly, Machine Learning Models of Vibrating H₂CO: Comparing Reproducing Kernels, FCHL and PhysNet, The Journal of Physical Chemistry A 124, 8853 (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.5281/zenodo.3911072 — binghuang2018/aqml-data: First release of aqml-data!, by Binghuang2018
Related MARVEL publication:
- B. Huang, O. A. von Lilienfeld, Quantum machine learning using atom-in-molecule-based fragments selected on the fly, Nature Chemistry 12, 945+ (2020). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.6084/m9.figshare.6994556 — Readme file, by A. S. Christensen
Related MARVEL publication:
- A. S. Christensen, F. A. Faber, O. A. von Lilienfeld, Operators in quantum machine learning: Response properties in chemical space, The Journal of Chemical Physics 150, 064105 (2019). [Open Access URL]
  Group(s): von Lilienfeld / Project(s): INC2
10.24435/materialscloud:2018.0014/v1 — Machine learning meets volcano plots: Computational discovery of cross-coupling catalysts, by B. Meyer, B. Sawatlon, S. N. Heinen, O. A. Von Lilienfeld, C. Corminboeuf
Related MARVEL publication:
- B. Meyer, B. Sawatlon, S. Heinen, O. A. von Lilienfeld, C. Corminboeuf, Machine learning meets volcano plots: computational discovery of cross-coupling catalysts, Chemical Science 9, 7069 (2018). [Open Access URL]
  Group(s): Corminboeuf, von Lilienfeld / Project(s): DD1, INC2