Learning graph representations with maximal cliques by Molaei, S, Bousejin, NG, Zare, H, Jalili, M, Pan, S

Deep node clustering based on mutual information maximization by Molaei, S, Ghanbari Bousejin, N, Zare, H, Jalili, M

Graph representation learning based on deep generative gaussian mixture models by Niknam, G, Molaei, S, Zare, H, Clifton, D, Pan, S

DyVGRNN: DYnamic mixture variational graph recurrent neural networks by Niknam, G, Molaei, S, Zare, H, Pan, S, Jalili, M, Zhu, T, Clifton, D

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks by Niknam, G, Molaei, S, Zare, H, Pan, S, Jalili, M, Zhu, T, Clifton, D

Temporal dynamics unleashed: elevating variational graph attention by Molaei, S, Niknam, G, Ghosheh, GO, Chauhan, VK, Zare, H, Zhu, T, Pan, S, Clifton, DA

Epigenetic targeting of bromodomain protein BRD4 counteracts cancer cachexia and prolongs survival by Segatto, M, Fittipaldi, R, Pin, F, Sartori, R, Dae Ko, K, Zare, H, Fenizia, C, Zanchettin, G, Pierobon, E, Hatakeyama, S, Sperti, C, Merigliano, S, Sandri, M, Filippakopoulos, P, Costelli, P, Sartorelli, V, Caretti, G

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults by Hofer, E, Roshchupkin, GV, Adams, HHH, Knol, MJ, Lin, H, Li, S, Zare, H, Ahmad, S, Armstrong, NJ, Satizabal, CL, Bernard, M, Bis, JC, Gillespie, NA, Luciano, M, Mishra, A, Scholz, M, Teumer, A, Xia, R, Jian, X, Mosley, TH, Saba, Y, Pirpamer, L, Seiler, S, Becker, JT, Carmichael, O, Rotter, JI, Psaty, BM, Lopez, OL, Amin, N, van der Lee, SJ, Yang, Q, Himali, JJ, Maillard, P, Beiser, AS, DeCarli, C, Karama, S, Lewis, L, Harris, M, Bastin, ME, Deary, IJ, Veronica Witte, A, Beyer, F, Loeffler, M, Mather, KA, Schofield, PR, Thalamuthu, A, Kwok, JB, Wright, MJ, Ames, D, Trollor, J, van Duijn, CM, Grabe, HJ, Longstreth Jr, WT, Fornage, M, Paus, T, Debette, S, Ikram, MA, Schmidt, H, Schmidt, R, Seshadr, S