Publications

2025

1. 

   Exploring the design space of machine-learning models for quantum chemistry with a fully differentiable framework

   Divya Suman, Jigyasa Nigam, Sandra Saade, Paolo Pegolo, Hanna Tuerk, Xing Zhang, Garnet Kin Chan, and Michele Ceriotti

   arXiv preprint arXiv:2504.01187, 2025

   Bib

   @article{suman2025exploring,
     title = {Exploring the design space of machine-learning models for quantum chemistry with a fully differentiable framework},
     url = {https://arxiv.org/abs/2504.01187},
     author = {Suman, Divya and Nigam, Jigyasa and Saade, Sandra and Pegolo, Paolo and Tuerk, Hanna and Zhang, Xing and Chan, Garnet Kin and Ceriotti, Michele},
     journal = {arXiv preprint arXiv:2504.01187},
     year = {2025},
     ham = {true}
   }

2024

1. 

   Integrating symmetry and physical constraints into atomic-scale machine learning

   Jigyasa Nigam

   2024

   Bib

   @article{thesis2024jn,
     title = {Integrating symmetry and physical constraints into atomic-scale machine learning},
     url = {https://infoscience.epfl.ch/handle/20.500.14299/240680},
     doi = {10.5075/epfl-thesis-10848},
     author = {Nigam, Jigyasa},
     year = {2024},
     keywords = {atom-centered density correlations (ACDC) | atomistic machine learning | descriptors | N-center representations | equivariance , completeness , physical constraints | electronic Hamiltonians},
   }

2. 

   Expanding density-correlation machine learning representations for anisotropic coarse-grained particles

   Arthur Lin, Kevin K Huguenin-Dumittan, Yong-Cheol Cho, Jigyasa Nigam, and Rose K Cersonsky

   The Journal of Chemical Physics, 2024

   Bib

   @article{lin2024expanding,
     title = {Expanding density-correlation machine learning representations for anisotropic coarse-grained particles},
     author = {Lin, Arthur and Huguenin-Dumittan, Kevin K and Cho, Yong-Cheol and Nigam, Jigyasa and Cersonsky, Rose K},
     journal = {The Journal of Chemical Physics},
     volume = {161},
     number = {7},
     year = {2024},
     publisher = {AIP Publishing},
     reps = {true}
   }

3. 

   Electronic Excited States from Physically Constrained Machine Learning

   Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, and Michele Ceriotti

   ACS Central Science, 2024

   Bib

   @article{cignoni2024electronic,
     title = {Electronic Excited States from Physically Constrained Machine Learning},
     author = {Cignoni, Edoardo and Suman, Divya and Nigam, Jigyasa and Cupellini, Lorenzo and Mennucci, Benedetta and Ceriotti, Michele},
     journal = {ACS Central Science},
     volume = {10},
     number = {3},
     pages = {637--648},
     year = {2024},
     publisher = {ACS Publications},
     ham = {true}
   }

4. 

   Completeness of atomic structure representations

   Jigyasa Nigam, Sergey N Pozdnyakov, Kevin K Huguenin-Dumittan, and Michele Ceriotti

   APL Machine Learning, 2024

   Bib

   @article{nigam2024completeness,
     title = {Completeness of atomic structure representations},
     author = {Nigam, Jigyasa and Pozdnyakov, Sergey N and Huguenin-Dumittan, Kevin K and Ceriotti, Michele},
     journal = {APL Machine Learning},
     volume = {2},
     number = {1},
     year = {2024},
     publisher = {AIP Publishing},
     reps = {true}
   }

2022

1. 

   Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties

   Jigyasa Nigam, Michael J Willatt, and Michele Ceriotti

   The Journal of Chemical Physics, 2022

   Bib

   @article{nigam2022equivariant,
     title = {Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties},
     author = {Nigam, Jigyasa and Willatt, Michael J and Ceriotti, Michele},
     journal = {The Journal of Chemical Physics},
     volume = {156},
     number = {1},
     pages = {014115},
     year = {2022},
     publisher = {AIP Publishing LLC},
     ham = {true}
   }

2. 

   Unified theory of atom-centered representations and message-passing machine-learning schemes

   Jigyasa Nigam, Sergey Pozdnyakov, Guillaume Fraux, and Michele Ceriotti

   The Journal of Chemical Physics, 2022

   Bib

   @article{nigam2022unified,
     title = {Unified theory of atom-centered representations and message-passing machine-learning schemes},
     author = {Nigam, Jigyasa and Pozdnyakov, Sergey and Fraux, Guillaume and Ceriotti, Michele},
     journal = {The Journal of Chemical Physics},
     volume = {156},
     number = {20},
     pages = {204115},
     year = {2022},
     publisher = {AIP Publishing LLC},
     reps = {true}
   }

3. Roadmap on Machine Learning in Electronic Structure

   H J Kulik, T Hammerschmidt, J Schmidt, S Botti, M A L Marques, M Boley, M Scheffler, M Todorović, P Rinke, C Oses, A Smolyanyuk, S Curtarolo, A Tkatchenko, A P Bartók, S Manzhos, M Ihara, T Carrington, J Behler, O Isayev, M Veit, A Grisafi, J Nigam, M Ceriotti, K T Schütt, J Westermayr, M Gastegger, R J Maurer, B Kalita, K Burke, R Nagai, R Akashi, O Sugino, J Hermann, F Noé, S Pilati, C Draxl, M Kuban, S Rigamonti, M Scheidgen, M Esters, D Hicks, C Toher, P V Balachandran, I Tamblyn, S Whitelam, C Bellinger, and L M Ghiringhelli

   Electron. Struct., Jun 2022

   Bib

   @article{kuli+22es,
     title = {Roadmap on {{Machine}} Learning in Electronic Structure},
     author = {Kulik, H J and Hammerschmidt, T and Schmidt, J and Botti, S and Marques, M A L and Boley, M and Scheffler, M and Todorovi{\'c}, M and Rinke, P and Oses, C and Smolyanyuk, A and Curtarolo, S and Tkatchenko, A and Bart{\'o}k, A P and Manzhos, S and Ihara, M and Carrington, T and Behler, J and Isayev, O and Veit, M and Grisafi, A and Nigam, J and Ceriotti, M and Sch{\"u}tt, K T and Westermayr, J and Gastegger, M and Maurer, R J and Kalita, B and Burke, K and Nagai, R and Akashi, R and Sugino, O and Hermann, J and No{\'e}, F and Pilati, S and Draxl, C and Kuban, M and Rigamonti, S and Scheidgen, M and Esters, M and Hicks, D and Toher, C and Balachandran, P V and Tamblyn, I and Whitelam, S and Bellinger, C and Ghiringhelli, L M},
     year = {2022},
     month = jun,
     journal = {Electron. Struct.},
     volume = {4},
     number = {2},
     pages = {023004},
     issn = {2516-1075},
     doi = {10.1088/2516-1075/ac572f},
     urldate = {2022-08-23},
   }

2021

1. Optimal Radial Basis for Density-Based Atomic Representations

   Alexander Goscinski, Félix Musil, Sergey Pozdnyakov, Jigyasa Nigam, and Michele Ceriotti

   J. Chem. Phys., Jun 2021

   Bib

   @article{gosc+21jcp,
     title = {Optimal Radial Basis for Density-Based Atomic Representations},
     author = {Goscinski, Alexander and Musil, F{\'e}lix and Pozdnyakov, Sergey and Nigam, Jigyasa and Ceriotti, Michele},
     year = {2021},
     journal = {J. Chem. Phys.},
     volume = {155},
     number = {10},
     pages = {104106},
     doi = {10.1063/5.0057229},
   }

2. 

   Multi-scale approach for the prediction of atomic scale properties

   Andrea Grisafi, Jigyasa Nigam, and Michele Ceriotti

   Chemical Science, Jun 2021

   Bib

   @article{grisafi2021multi,
     title = {Multi-scale approach for the prediction of atomic scale properties},
     author = {Grisafi, Andrea and Nigam, Jigyasa and Ceriotti, Michele},
     journal = {Chemical Science},
     volume = {12},
     number = {6},
     pages = {2078--2090},
     year = {2021},
     publisher = {Royal Society of Chemistry},
     reps = {true},
   }

2020

1. 

   Recursive evaluation and iterative contraction of N-body equivariant features

   Jigyasa Nigam, Sergey Pozdnyakov, and Michele Ceriotti

   The Journal of Chemical Physics, Jun 2020

   Bib

   @article{nigam2020recursive,
     title = {Recursive evaluation and iterative contraction of N-body equivariant features},
     author = {Nigam, Jigyasa and Pozdnyakov, Sergey and Ceriotti, Michele},
     journal = {The Journal of Chemical Physics},
     volume = {153},
     number = {12},
     pages = {121101},
     year = {2020},
     publisher = {AIP Publishing LLC},
     reps = {true},
   }