• Cosmology with the Laser Interferometer Space Antenna 

  Auclair, P; Bacon, D; Baker, T; Barreiro, T; Bartolo, N; Belgacem, E; Bellomo, N; Ben-Dayan, I; Bertacca, D; Besancon, M (Springer Nature, 2023-12-01)

  The Laser Interferometer Space Antenna (LISA) has two scientific objectives of cosmological focus: to probe the expansion rate of the universe, and to understand stochastic gravitational-wave backgrounds and their implications ...

• The structure of segregation in co-authorship networks and its impact on scientific production 

  Perra, N; Jamarillo, AM; Williams, HTP; Menezes, R

• The Concept of Decentralization Through Time and Disciplines: A Quantitative Exploration 

  Perra, N; Di Bona, G; Latora, V; Bracci, A; Baronchelli, A

• Quantifying the uncertainty of partitions for infinite mixture models 

  Lavigne, A; Liverani, S (Elsevier, 2023)

  Bayesian clustering models, such as Dirichlet process mixture models (DPMMs), are sophisticated flexible models. They induce a posterior distribution on the set of all partitions of a set of observations. Analysing this ...

• Neuroscience Needs Network Science. 

  Barabási, DL; Bianconi, G; Bullmore, E; Burgess, M; Chung, S; Eliassi-Rad, T; George, D; Kovács, IA; Makse, H; Nichols, TE (The Society for Neuroscience, 2023-08-23)

  The brain is a complex system comprising a myriad of interacting neurons, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying ...

• Neuroscience needs Network Science 

  Barabási, DL; Bianconi, G; Bullmore, E; Burgess, M; Chung, S; Eliassi-Rad, T; George, D; Kovács, IA; Makse, H; Papadimitriou, C (Society for Neuroscience, 2023-08-23)

• Sets of non-Lyapunov behaviour for scalar and matrix Schrödinger cocycles 

  Goldsheid, I; Sodin, A (Oxford University Press, 2023-09-01)

• Emotional experiences and psychological well-being in 51 countries during the COVID-19 pandemic. 

  Sun, R; Balabanova, A; Bajada, CJ; Liu, Y; Kriuchok, M; Voolma, S-R; Đurić, M; Mayer, C-H; Constantinou, M; Chichua, M (2023-08-24)

  The COVID-19 pandemic presents challenges to psychological well-being, but how can we predict when people suffer or cope during sustained stress? Here, we test the prediction that specific types of momentary emotional ...

• Modeling self-propagating malware with epidemiological models 

  Chernikova, A; Gozzi, N; Perra, N; Boboila, S; Eliassi-Rad, T; Oprea, A

• Bifractality of fractal scale-free networks 

  Yamamoto, Jun; Yakubo, Kousuke (American Physical Society, 2023-08)

• Learning Regularization Parameter-Maps for Variational Image Reconstruction using Deep Neural Networks and Algorithm Unrolling 

  Kofler, A; Altekrüger, F; Ba, FA; Kolbitsch, C; Papoutsellis, E; Schote, D; Sirotenko, C; Zimmermann, FF; Papafitsoros, K (2023-01-14)

• Oscillon formation during inflationary preheating with general relativity 

  Aurrekoetxea, JC; Clough, K; Muia, F (2023-07-15)

  We study the nonperturbative evolution of inflationary fluctuations during preheating using fully nonlinear general-relativistic field-theory simulations. We choose a single-field inflationary model that is consistent with ...

• Skew Schur function representation of directed paths in a slit 

  Khalid, A; Prellberg, T (2021)

• LARGE SIMPLICIAL COMPLEXES: UNIVERSALITY, RANDOMNESS, AND AMPLENESS 

  Farber, M

• On the universality class of the special adsorption point of two-dimensional lattice polymers 

  Rodrigues, NT; Oliveira, TJ; Prellberg, T (2023-05-16)

• Lasso and elastic nets by orthants 

  Maruri-Aguilar, H (2023-07-21)

• The small cycle counts of random feedback shift registers 

  Stark, D (2023)

• Persistent Dirac for molecular representation 

  Wee, J; Bianconi, G; Xia, K (2023)

• A universal null-distribution for topological data analysis 

  Bobrowski, O; Skraba, P (2023)

• Machine learning approaches for the optimization of packing densities in granular matter 

  Baule, A; Kurban, E; Liu, K; Makse, HA (2023)

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