DOI,IST REx ID,Title of publication
10.1103/physrevd.101.083016,17591,Probing gaseous galactic halos through the rotational kinematic Sunyaev-Zeldovich effect
10.1093/mnras/staa3057,17595,Suppression of H2 cooling in protogalaxies aided by trapped Lyα cooling radiation
10.3847/1538-4357/ab91b4,17596,Cosmic evolution of stellar-mass black hole merger rate in active galactic nuclei
10.1103/physrevd.102.123506,17597,Interpreting deep learning models for weak lensing
10.1016/j.newar.2020.101525,17600,The quest for dual and binary supermassive black holes: A multi-messenger view
10.3847/1538-4357/abab95,17601,Circumbinary disks: Accretion and torque as a function of mass ratio and disk viscosity
10.3847/1538-4357/aba432,17604,Gas-driven inspiral of binaries in thin accretion disks
10.3847/2041-8213/ab745d,17605,GW170817A as a hierarchical black hole merger
10.3847/2041-8213/abb940,17607,Black hole formation in the lower mass gap through mergers and accretion in AGN disks
10.1021/acs.nanolett.0c01956,17908,Mechanically tunable quantum interference in ferrocene-based single-molecule junctions
10.1039/d0nr00467g,17911,Unsupervised feature recognition in single-molecule break junction data
10.1103/physreva.102.063316,18194,Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles
10.1109/tpami.2020.2994507,18228,Horizontal flows and manifold stochastics in geometric deep learning
10.1109/ijcnn48605.2020.9206968,18247,Feature map transform coding for energy-efficient CNN inference
10.1109/icassp40776.2020.9054542,18249,Joint learning of cartesian undersampling and reconstruction for accelerated MRI
10.1109/tvcg.2018.2867513,18250,Hamiltonian operator for spectral shape analysis
10.1128/mbio.00705-20,18253,Access to PCNA by Srs2 and Elg1 controls the choice between alternative repair pathways in Saccharomyces cerevisiae
10.1109/iccvw.2019.00567,18255,Learning to detect and retrieve objects from unlabeled videos
10.1109/cvpr.2019.00671,18259,Laso: Label-set operations networks for multi-label few-shot learning
10.1007/s00222-020-00964-9,22054,Invariance of white noise for KdV on the line