Pan Kessel

1.3k total citations · 1 hit paper
20 papers, 673 citations indexed

About

Pan Kessel is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Condensed Matter Physics. According to data from OpenAlex, Pan Kessel has authored 20 papers receiving a total of 673 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistical and Nonlinear Physics, 6 papers in Artificial Intelligence and 5 papers in Condensed Matter Physics. Recurrent topics in Pan Kessel's work include Theoretical and Computational Physics (5 papers), Model Reduction and Neural Networks (4 papers) and Black Holes and Theoretical Physics (4 papers). Pan Kessel is often cited by papers focused on Theoretical and Computational Physics (5 papers), Model Reduction and Neural Networks (4 papers) and Black Holes and Theoretical Physics (4 papers). Pan Kessel collaborates with scholars based in Germany, Japan and South Korea. Pan Kessel's co-authors include Kim A. Nicoli, Alexandre Tkatchenko, Michael Gastegger, K. Müller, Kristof T. Schütt, Shinichi Nakajima, Evgeny Skvortsov, Massimo Taronna, Christopher J. Anders and Klaus‐Robert Müller and has published in prestigious journals such as Physical Review Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and Geophysical Journal International.

In The Last Decade

Pan Kessel

19 papers receiving 668 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SchNetPack: A Deep Learning Toolbox For Atomistic Systems

2018 305 citations Kristof T. Schütt, Pan Kessel et al. Journal of Chemical Theory and Computation profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Pan Kessel Germany	11	295	153	139	124	116	20	673
Kim A. Nicoli Germany	6	294 1.0×	36 0.2×	134 1.0×	51 0.4×	69 0.6×	9	476
V. Hnizdo United States	19	98 0.3×	517 3.4×	109 0.8×	166 1.3×	66 0.6×	75	1.2k
D.A. Johnston United Kingdom	20	142 0.5×	277 1.8×	78 0.6×	542 4.4×	30 0.3×	101	1.2k
Sergio Caracciolo Italy	22	215 0.7×	539 3.5×	130 0.9×	378 3.0×	68 0.6×	121	1.9k
Guglielmo Mazzola Switzerland	20	158 0.5×	25 0.2×	63 0.5×	45 0.4×	453 3.9×	33	947
Károly F. Pál Hungary	20	67 0.2×	264 1.7×	70 0.5×	179 1.4×	438 3.8×	55	1.1k
C. A. A. de Carvalho Brazil	13	39 0.1×	222 1.5×	48 0.3×	205 1.7×	129 1.1×	69	1.0k
Nicolas Sourlas France	15	235 0.8×	360 2.4×	99 0.7×	555 4.5×	66 0.6×	22	1.6k
École d'été de physique théorique	13	246 0.8×	97 0.6×	11 0.1×	142 1.1×	79 0.7×	66	757
I. J. Zucker United Kingdom	23	172 0.6×	90 0.6×	43 0.3×	172 1.4×	30 0.3×	60	1.3k

Countries citing papers authored by Pan Kessel

Since Specialization

Citations

This map shows the geographic impact of Pan Kessel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pan Kessel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pan Kessel more than expected).

Fields of papers citing papers by Pan Kessel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pan Kessel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pan Kessel. The network helps show where Pan Kessel may publish in the future.

Co-authorship network of co-authors of Pan Kessel

This figure shows the co-authorship network connecting the top 25 collaborators of Pan Kessel. A scholar is included among the top collaborators of Pan Kessel based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pan Kessel. Pan Kessel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Dreyer, Frédéric A., Jan Ludwiczak, Brennan Abanades, et al.. (2025). Conformation-aware structure prediction of antigen-recognizing immune proteins. mAbs. 18(1). 2602217–2602217.

Bacchio, Simone, et al.. (2023). Learning trivializing gradient flows for lattice gauge theories. Physical review. D. 107(5). 21 indexed citations

Nicoli, Kim A., Christopher J. Anders, Tobias Hartung, et al.. (2023). Detecting and mitigating mode-collapse for flow-based sampling of lattice field theories. Physical review. D. 108(11). 15 indexed citations

Nicoli, Kim A., Christopher J. Anders, Lena Funcke, et al.. (2023). NeuLat: a toolbox for neural samplers in lattice field theories. Proceedings Of Science. 286–286. 1 indexed citations

Müller, Klaus‐Robert, et al.. (2023). Diffeomorphic Counterfactuals With Generative Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(5). 3257–3274. 5 indexed citations

Nicoli, Kim A., et al.. (2022). Gradients should stay on path: better estimators of the reverse- and forward KL divergence for normalizing flows. Machine Learning Science and Technology. 3(4). 45006–45006. 9 indexed citations

Nicoli, Kim A., Christopher J. Anders, Lena Funcke, et al.. (2022). Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse. Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021). 338–338. 10 indexed citations

Kessel, Pan, et al.. (2021). Diffeomorphic Explanations with Normalizing Flows. International Conference on Machine Learning. 2 indexed citations

Nicoli, Kim A., Christopher J. Anders, Lena Funcke, et al.. (2021). Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models. Physical Review Letters. 126(3). 32001–32001. 71 indexed citations

10.

Anders, Christopher J., et al.. (2021). Towards robust explanations for deep neural networks. Pattern Recognition. 121. 108194–108194. 28 indexed citations

11.

Tosi, Nicola, et al.. (2021). Toward Constraining Mars' Thermal Evolution Using Machine Learning. Earth and Space Science. 8(4). 7 indexed citations

12.

Tosi, Nicola, et al.. (2021). Deep learning for surrogate modeling of two-dimensional mantle convection. Physical Review Fluids. 6(11). 8 indexed citations

13.

Tosi, Nicola, et al.. (2020). A machine-learning-based surrogate model of Mars’ thermal evolution. Geophysical Journal International. 222(3). 1656–1670. 7 indexed citations

14.

Nicoli, Kim A., Shinichi Nakajima, Nils Strodthoff, et al.. (2020). Asymptotically unbiased estimation of physical observables with neural samplers. Physical review. E. 101(2). 23304–23304. 63 indexed citations

15.

Alber, Maximilian, et al.. (2019). Explanations can be manipulated and geometry is to blame. Neural Information Processing Systems. 32. 13567–13578. 10 indexed citations

16.

Kessel, Pan & Karapet Mkrtchyan. (2018). Cubic interactions of massless bosonic fields in three dimensions. II. Parity-odd and Chern-Simons vertices. Physical review. D. 97(10). 18 indexed citations

17.

Schütt, Kristof T., Pan Kessel, Michael Gastegger, et al.. (2018). SchNetPack: A Deep Learning Toolbox For Atomistic Systems. Journal of Chemical Theory and Computation. 15(1). 448–455. 305 indexed citations breakdown →

18.

Kessel, Pan. (2017). The very basics of higher-spin theory. 1–1. 6 indexed citations

19.

Boulanger, Nicolas, Pan Kessel, Evgeny Skvortsov, & Massimo Taronna. (2016). Higher spin interactions in four-dimensions: Vasiliev versus Fronsdal. Journal of Physics A Mathematical and Theoretical. 49(9). 95402–95402. 63 indexed citations

20.

Kessel, Pan, et al.. (2015). Higher spins and matter interacting in dimension three. Journal of High Energy Physics. 2015(11). 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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