N. Rahaman et al., “Dynamic inference with neural interpreters,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 10985–10998.

B. Scholkopf et al., “Toward causal representation learning,” Proceedings of the IEEE, vol. 109, no. 5. Institute of Electrical and Electronics Engineers, pp. 612–634, 2021.

A. Dittadi et al., “On the transfer of disentangled representations in realistic settings,” in The Ninth International Conference on Learning Representations, Virtual, 2021.

F. Locatello, “Enforcing and discovering structure in machine learning,” arXiv. .

F. Träuble et al., “Representation learning for out-of-distribution generalization in reinforcement learning,” in ICML 2021 Workshop on Unsupervised Reinforcement Learning, Virtual, 2021.

I. Koval, “Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse,” arXiv. .

V. Toman, “Improved verification techniques for concurrent systems,” Institute of Science and Technology Austria, 2021.

M. Patxot et al., “Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits,” Nature Communications, vol. 12, no. 1. Springer Nature, 2021.

K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.

K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.

K. Chatterjee, W. Dvoák, M. H. Henzinger, and A. Svozil, “Algorithms and conditional lower bounds for planning problems,” Artificial Intelligence, vol. 297, no. 8. Elsevier, 2021.

M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.

Y. Zhang et al., “Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride,” Chemical Engineering Journal, vol. 418, no. 8. Elsevier, 2021.

K. T. Baldwin et al., “HepaCAM controls astrocyte self-organization and coupling,” Neuron, vol. 109, no. 15. Elsevier, p. 2427–2442.e10, 2021.

Y. Zhang et al., “Doping-mediated stabilization of copper vacancies to promote thermoelectric properties of Cu2-xS,” Nano Energy, vol. 85, no. 7. Elsevier, 2021.

N. Cavallari, C. Artner, and E. Benková, “Auxin-regulated lateral root organogenesis,” Cold Spring Harbor Perspectives in Biology, vol. 13, no. 7. Cold Spring Harbor Laboratory Press, 2021.

K. Picard et al., “Microglial-glucocorticoid receptor depletion alters the response of hippocampal microglia and neurons in a chronic unpredictable mild stress paradigm in female mice,” Brain, Behavior, and Immunity, vol. 97. Elsevier, pp. 423–439, 2021.

M. Li et al., “PbS–Pb–CuxS composites for thermoelectric application,” ACS Applied Materials and Interfaces, vol. 13, no. 43. American Chemical Society , pp. 51373–51382, 2021.

M. Li et al., “Effect of the annealing atmosphere on crystal phase and thermoelectric properties of copper sulfide,” ACS Nano, vol. 15, no. 3. American Chemical Society , pp. 4967–4978, 2021.

G. F. Osang, H. Edelsbrunner, and M. Saadatfar, “Topological signatures and stability of hexagonal close packing and Barlow stackings,” Soft Matter, vol. 17, no. 40. Royal Society of Chemistry , pp. 9107–9115, 2021.