Zadaianchuk, Andrii, et al. “Unsupervised Semantic Segmentation with Self-Supervised Object-Centric Representations.” The 11th International Conference on Learning Representations, 2023.

Faller, Philipp M., et al. “Self-Compatibility: Evaluating Causal Discovery without Ground Truth.”10.48550/arXiv.2307.09552__ArXiv, 2307.09552, doi:10.48550/arXiv.2307.09552.

Boocock, Daniel R., et al. “Interplay between Mechanochemical Patterning and Glassy Dynamics in Cellular Monolayers.”10.1103/prxlife.1.013001__PRX Life, vol. 1, no. 1, 013001, American Physical Society, 2023, doi:10.1103/prxlife.1.013001.

Nardin, Michele, et al. “Theta Oscillations as a Substrate for Medial Prefrontal-Hippocampal Assembly Interactions.”10.1016/j.celrep.2023.113015__Cell Reports, vol. 42, no. 9, 113015, Elsevier, 2023, doi:10.1016/j.celrep.2023.113015.

Cho, Ukrae H., and Martin Hetzer. “Caspase-Mediated Nuclear Pore Complex Trimming in Cell Differentiation and Endoplasmic Reticulum Stress.”10.7554/eLife.89066__ELife, vol. 12, 6, eLife Sciences Publications, 2023, doi:10.7554/eLife.89066.

Anastos, Michael, et al. “Splitting Matchings and the Ryser-Brualdi-Stein Conjecture for Multisets.”10.37236/11714__Electronic Journal of Combinatorics, vol. 30, no. 3, .10, Electronic Journal of Combinatorics, 2023, doi:10.37236/11714.

Sun, Yican, et al. “Automated Tail Bound Analysis for Probabilistic Recurrence Relations.”10.1007/978-3-031-37709-9_2__Computer Aided Verification, vol. 13966, Springer Nature, 2023, pp. 16–39, doi:10.1007/978-3-031-37709-9_2.

Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”10.1007/978-3-031-37709-9_5__International Conference on Computer Aided Verification, vol. 13966, Springer Nature, 2023, pp. 86–112, doi:10.1007/978-3-031-37709-9_5.

Nagano, Makoto, et al. “Distinct Role of TGN-Resident Clathrin Adaptors for Vpp Activation in the TGN-Endosome Trafficking Pathway.”10.1242/jcs.261448__Journal of Cell Science, vol. 136, no. 17, j48, The Company of Biologists, 2023, doi:10.1242/jcs.261448.

Henderson, Paul M., et al. “Deep Learning Extraction of Band Structure Parameters from Density of States: A Case Study on Trilayer Graphene.”10.1103/physrevb.108.125411__Physical Review B, vol. 108, no. 12, 125411, American Physical Society, 2023, doi:10.1103/physrevb.108.125411.