Unsupervised feature recognition in single-molecule break junction data
A. Magyarkuti, N. Balogh, Z. Balogh, L. Venkataraman, A. Halbritter, Nanoscale 12 (2020) 8355–8363.

Gold–carbon contacts from oxidative addition of aryl iodides
R.L. Starr, T. Fu, E.A. Doud, I. Stone, X. Roy, L. Venkataraman, Journal of the American Chemical Society 142 (2020) 7128–7133.

Visualizing quantum interference in molecular junctions
S. Gunasekaran, J.E. Greenwald, L. Venkataraman, Nano Letters 20 (2020) 2843–2848.

Solitonics with polyacetylenes
D. Hernangómez-Pérez, S. Gunasekaran, L. Venkataraman, F. Evers, Nano Letters 20 (2020) 2615–2619.

Fractional Chern insulators of few bosons in a box: Hall plateaus from center-of-mass drifts and density profiles
C. Repellin, J. Leonard, N. Goldman, Physical Review A 102 (2020).

Horizontal flows and manifold stochastics in geometric deep learning
S. Sommer, A.M. Bronstein, IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (2020) 811–822.

Intel® RealSense  coded light depth camera
A. Zabatani, V. Surazhsky, E. Sperling, S.B. Moshe, O. Menashe, D.H. Silver, Z. Karni, A.M. Bronstein, M.K. Bronstein, R. Kimmel, IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (2020) 2333–2345.

Generating adversarial surfaces via bandlimited perturbations
G. Mariani, L. Cosmo, A.M. Bronstein, E. Rodolà, Computer Graphics Forum 39 (2020) 253–264.

Feature map transform coding for energy-efficient CNN inference
B. Chmiel, C. Baskin, E. Zheltonozhskii, R. Banner, Y. Yermolin, A. Karbachevsky, A.M. Bronstein, A. Mendelson, in:, 2020 International Joint Conference on Neural Networks (IJCNN), IEEE, 2020.

Self-supervised object detection and retrieval using unlabeled videos
E. Amrani, R. Ben-Ari, I. Shapira, T. Hakim, A.M. Bronstein, in:, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 2020.

Joint learning of cartesian undersampling and reconstruction for accelerated MRI
T. Weiss, S. Vedula, O. Senouf, O. Michailovich, M. Zibulevsky, A.M. Bronstein, in:, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2020.

Hamiltonian operator for spectral shape analysis
Y. Choukroun, A. Shtern, A.M. Bronstein, R. Kimmel, IEEE Transactions on Visualization and Computer Graphics 26 (2020) 1320–1331.

3D FLAT: Feasible learned acquisition trajectories for accelerated MRI
J. Alush-Aben, L. Ackerman-Schraier, T. Weiss, S. Vedula, O. Senouf, A.M. Bronstein, in:, International Workshop on Machine Learning for Medical Image Reconstruction, Springer Nature, 2020, pp. 3–16.

Overparameterized models for vector fields
K. Rotker, D.B. Bashat, A.M. Bronstein, SIAM Journal on Imaging Sciences 13 (2020) 1386–1414.

Access to PCNA by Sr and El controls the choice between alternative repair pathways in Saccharomyces cerevisiae
M. Arbel, A.M. Bronstein, S. Sau, B. Liefshitz, M. Kupiec, MBio 11 (2020).

Learning to detect and retrieve objects from unlabeled videos
E. Amrani, R. Ben-Ari, T. Hakim, A.M. Bronstein, in:, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), IEEE, 2020.

Repmet: Representative-based metric learning for classification and few-shot object detection
L. Karlinsky, J. Shtok, S. Harary, E. Schwartz, A. Aides, R. Feris, R. Giryes, A.M. Bronstein, in:, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2020.

Laso: Label-set operations networks for multi-label few-shot learning
A. Alfassy, L. Karlinsky, A. Aides, J. Shtok, S. Harary, R. Feris, R. Giryes, A.M. Bronstein, in:, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2020.

Unsupervised learning of dense shape correspondence
O. Halimi, O. Litany, E.R. Rodola, A.M. Bronstein, R. Kimmel, in:, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2020.

Primitive divisors of sequences associated to elliptic curves
M. Verzobio, Journal of Number Theory 209 (2020) 378–390.