@inproceedings{8600,
  abstract     = {A vector addition system with states (VASS) consists of a finite set of states and counters. A transition changes the current state to the next state, and every counter is either incremented, or decremented, or left unchanged. A state and value for each counter is a configuration; and a computation is an infinite sequence of configurations with transitions between successive configurations. A probabilistic VASS consists of a VASS along with a probability distribution over the transitions for each state. Qualitative properties such as state and configuration reachability have been widely studied for VASS. In this work we consider multi-dimensional long-run average objectives for VASS and probabilistic VASS. For a counter, the cost of a configuration is the value of the counter; and the long-run average value of a computation for the counter is the long-run average of the costs of the configurations in the computation. The multi-dimensional long-run average problem given a VASS and a threshold value for each counter, asks whether there is a computation such that for each counter the long-run average value for the counter does not exceed the respective threshold. For probabilistic VASS, instead of the existence of a computation, we consider whether the expected long-run average value for each counter does not exceed the respective threshold. Our main results are as follows: we show that the multi-dimensional long-run average problem (a) is NP-complete for integer-valued VASS; (b) is undecidable for natural-valued VASS (i.e., nonnegative counters); and (c) can be solved in polynomial time for probabilistic integer-valued VASS, and probabilistic natural-valued VASS when all computations are non-terminating.},
  author       = {Chatterjee, Krishnendu and Henzinger, Thomas A and Otop, Jan},
  booktitle    = {31st International Conference on Concurrency Theory},
  isbn         = {9783959771603},
  issn         = {1868-8969},
  location     = {Virtual},
  publisher    = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
  title        = {{Multi-dimensional long-run average problems for vector addition systems with states}},
  doi          = {10.4230/LIPIcs.CONCUR.2020.23},
  volume       = {171},
  year         = {2020},
}

@article{8607,
  abstract     = {Clathrin-mediated endocytosis (CME) and its core endocytic machinery are evolutionarily conserved across all eukaryotes. In mammals, the heterotetrameric adaptor protein complex-2 (AP-2) sorts plasma membrane (PM) cargoes into vesicles through the recognition of motifs based on tyrosine or di-leucine in their cytoplasmic tails. However, in plants, very little is known on how PM proteins are sorted for CME and whether similar motifs are required. In Arabidopsis thaliana, the brassinosteroid (BR) receptor, BR INSENSITIVE1 (BRI1), undergoes endocytosis that depends on clathrin and AP-2. Here we demonstrate that BRI1 binds directly to the medium AP-2 subunit, AP2M. The cytoplasmic domain of BRI1 contains five putative canonical surface-exposed tyrosine-based endocytic motifs. The tyrosine-to-phenylalanine substitution in Y898KAI reduced BRI1 internalization without affecting its kinase activity. Consistently, plants carrying the BRI1Y898F mutation were hypersensitive to BRs. Our study demonstrates that AP-2-dependent internalization of PM proteins via the recognition of functional tyrosine motifs also operates in plants.},
  author       = {Liu, D and Kumar, R and LAN, Claus and Johnson, Alexander J and Siao, W and Vanhoutte, I and Wang, P and Bender, KW and Yperman, K and Martins, S and Zhao, X and Vert, G and Van Damme, D and Friml, Jiří and Russinova, E},
  issn         = {1532-298x},
  journal      = {Plant Cell},
  number       = {11},
  pages        = {3598--3612},
  publisher    = {American Society of Plant Biologists},
  title        = {{Endocytosis of BRASSINOSTEROID INSENSITIVE1 is partly driven by a canonical tyrosine-based Motif}},
  doi          = {10.1105/tpc.20.00384},
  volume       = {32},
  year         = {2020},
}

@article{8634,
  abstract     = {In laboratory studies and numerical simulations, we observe clear signatures of unstable time-periodic solutions in a moderately turbulent quasi-two-dimensional flow. We validate the dynamical relevance of such solutions by demonstrating that turbulent flows in both experiment and numerics transiently display time-periodic dynamics when they shadow unstable periodic orbits (UPOs). We show that UPOs we computed are also statistically significant, with turbulent flows spending a sizable fraction of the total time near these solutions. As a result, the average rates of energy input and dissipation for the turbulent flow and frequently visited UPOs differ only by a few percent.},
  author       = {Suri, Balachandra and Kageorge, Logan and Grigoriev, Roman O. and Schatz, Michael F.},
  issn         = {1079-7114},
  journal      = {Physical Review Letters},
  keywords     = {General Physics and Astronomy},
  number       = {6},
  publisher    = {American Physical Society},
  title        = {{Capturing turbulent dynamics and statistics in experiments with unstable periodic orbits}},
  doi          = {10.1103/physrevlett.125.064501},
  volume       = {125},
  year         = {2020},
}

@article{8645,
  abstract     = {Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a ‘combinatorially complete dataset’. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets. We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199 847 053 unique combinatorially complete genotype combinations of dimensionality ranging from 2 to 12. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data.},
  author       = {Esteban, Laura A and Lonishin, Lyubov R and Bobrovskiy, Daniil M and Leleytner, Gregory and Bogatyreva, Natalya S and Kondrashov, Fyodor and Ivankov, Dmitry N },
  issn         = {1460-2059},
  journal      = {Bioinformatics},
  number       = {6},
  pages        = {1960--1962},
  publisher    = {Oxford University Press},
  title        = {{HypercubeME: Two hundred million combinatorially complete datasets from a single experiment}},
  doi          = {10.1093/bioinformatics/btz841},
  volume       = {36},
  year         = {2020},
}

@article{8652,
  abstract     = {Nature creates electrons with two values of the spin projection quantum number. In certain applications, it is important to filter electrons with one spin projection from the rest. Such filtering is not trivial, since spin-dependent interactions are often weak, and cannot lead to any substantial effect. Here we propose an efficient spin filter based upon scattering from a two-dimensional crystal, which is made of aligned point magnets. The polarization of the outgoing electron flux is controlled by the crystal, and reaches maximum at specific values of the parameters. In our scheme, polarization increase is accompanied by higher reflectivity of the crystal. High transmission is feasible in scattering from a quantum cavity made of two crystals. Our findings can be used for studies of low-energy spin-dependent scattering from two-dimensional ordered structures made of magnetic atoms or aligned chiral molecules.},
  author       = {Ghazaryan, Areg and Lemeshko, Mikhail and Volosniev, Artem},
  issn         = {2399-3650},
  journal      = {Communications Physics},
  publisher    = {Springer Nature},
  title        = {{Filtering spins by scattering from a lattice of point magnets}},
  doi          = {10.1038/s42005-020-00445-8},
  volume       = {3},
  year         = {2020},
}

@article{8670,
  abstract     = {The α–z Rényi relative entropies are a two-parameter family of Rényi relative entropies that are quantum generalizations of the classical α-Rényi relative entropies. In the work [Adv. Math. 365, 107053 (2020)], we decided the full range of (α, z) for which the data processing inequality (DPI) is valid. In this paper, we give algebraic conditions for the equality in DPI. For the full range of parameters (α, z), we give necessary conditions and sufficient conditions. For most parameters, we give equivalent conditions. This generalizes and strengthens the results of Leditzky et al. [Lett. Math. Phys. 107, 61–80 (2017)].},
  author       = {Zhang, Haonan},
  issn         = {0022-2488},
  journal      = {Journal of Mathematical Physics},
  number       = {10},
  publisher    = {AIP Publishing},
  title        = {{Equality conditions of data processing inequality for α-z Rényi relative entropies}},
  doi          = {10.1063/5.0022787},
  volume       = {61},
  year         = {2020},
}

@article{8671,
  abstract     = {We study relations between evidence theory and S-approximation spaces. Both theories have their roots in the analysis of Dempsterchr('39')s multivalued mappings and lower and upper probabilities, and have close relations to rough sets. We show that an S-approximation space, satisfying a monotonicity condition, can induce a natural belief structure which is a fundamental block in evidence theory. We also demonstrate that one can induce a natural belief structure on one set, given a belief structure on another set, if the two sets are related by a partial monotone S-approximation space. },
  author       = {Shakiba, A. and Goharshady, Amir Kafshdar and Hooshmandasl, M.R. and Alambardar Meybodi, M.},
  issn         = {2008-9473},
  journal      = {Iranian Journal of Mathematical Sciences and Informatics},
  number       = {2},
  pages        = {117--128},
  publisher    = {Iranian Academic Center for Education, Culture and Research},
  title        = {{A note on belief structures and s-approximation spaces}},
  doi          = {10.29252/ijmsi.15.2.117},
  volume       = {15},
  year         = {2020},
}

@article{8672,
  abstract     = {Cell fate transitions are key to development and homeostasis. It is thus essential to understand the cellular mechanisms controlling fate transitions. Cell division has been implicated in fate decisions in many stem cell types, including neuronal and epithelial progenitors. In other stem cells, such as embryonic stem (ES) cells, the role of division remains unclear. Here, we show that exit from naive pluripotency in mouse ES cells generally occurs after a division. We further show that exit timing is strongly correlated between sister cells, which remain connected by cytoplasmic bridges long after division, and that bridge abscission progressively accelerates as cells exit naive pluripotency. Finally, interfering with abscission impairs naive pluripotency exit, and artificially inducing abscission accelerates it. Altogether, our data indicate that a switch in the division machinery leading to faster abscission regulates pluripotency exit. Our study identifies abscission as a key cellular process coupling cell division to fate transitions.},
  author       = {Chaigne, Agathe and Labouesse, Céline and White, Ian J. and Agnew, Meghan and Hannezo, Edouard B and Chalut, Kevin J. and Paluch, Ewa K.},
  issn         = {1878-1551},
  journal      = {Developmental Cell},
  number       = {2},
  pages        = {195--208},
  publisher    = {Elsevier},
  title        = {{Abscission couples cell division to embryonic stem cell fate}},
  doi          = {10.1016/j.devcel.2020.09.001},
  volume       = {55},
  year         = {2020},
}

@article{8679,
  abstract     = {A central goal of artificial intelligence in high-stakes decision-making applications is to design a single algorithm that simultaneously expresses generalizability by learning coherent representations of their world and interpretable explanations of its dynamics. Here, we combine brain-inspired neural computation principles and scalable deep learning architectures to design compact neural controllers for task-specific compartments of a full-stack autonomous vehicle control system. We discover that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. This system shows superior generalizability, interpretability and robustness compared with orders-of-magnitude larger black-box learning systems. The obtained neural agents enable high-fidelity autonomy for task-specific parts of a complex autonomous system.},
  author       = {Lechner, Mathias and Hasani, Ramin and Amini, Alexander and Henzinger, Thomas A and Rus, Daniela and Grosu, Radu},
  issn         = {2522-5839},
  journal      = {Nature Machine Intelligence},
  pages        = {642--652},
  publisher    = {Springer Nature},
  title        = {{Neural circuit policies enabling auditable autonomy}},
  doi          = {10.1038/s42256-020-00237-3},
  volume       = {2},
  year         = {2020},
}

@article{8680,
  abstract     = {Animal development entails the organization of specific cell types in space and time, and spatial patterns must form in a robust manner. In the zebrafish spinal cord, neural progenitors form stereotypic patterns despite noisy morphogen signaling and large-scale cellular rearrangements during morphogenesis and growth. By directly measuring adhesion forces and preferences for three types of endogenous neural progenitors, we provide evidence for the differential adhesion model in which differences in intercellular adhesion mediate cell sorting. Cell type–specific combinatorial expression of different classes of cadherins (N-cadherin, cadherin 11, and protocadherin 19) results in homotypic preference ex vivo and patterning robustness in vivo. Furthermore, the differential adhesion code is regulated by the sonic hedgehog morphogen gradient. We propose that robust patterning during tissue morphogenesis results from interplay between adhesion-based self-organization and morphogen-directed patterning.},
  author       = {Tsai, Tony Y.-C. and Sikora, Mateusz K and Xia, Peng and Colak-Champollion, Tugba and Knaut, Holger and Heisenberg, Carl-Philipp J and Megason, Sean G.},
  issn         = {1095-9203},
  journal      = {Science},
  keywords     = {Multidisciplinary},
  number       = {6512},
  pages        = {113--116},
  publisher    = {American Association for the Advancement of Science},
  title        = {{An adhesion code ensures robust pattern formation during tissue morphogenesis}},
  doi          = {10.1126/science.aba6637},
  volume       = {370},
  year         = {2020},
}

@article{8691,
  abstract     = {Given l>2ν>2d≥4, we prove the persistence of a Cantor--family of KAM tori of measure O(ε1/2−ν/l) for any non--degenerate nearly integrable Hamiltonian system of class Cl(D×Td), where D⊂Rd is a bounded domain, provided that the size ε of the perturbation is sufficiently small. This extends a result by D. Salamon in \cite{salamon2004kolmogorov} according to which we do have the persistence of a single KAM torus in the same framework. Moreover, it is well--known that, for the persistence of a single torus, the regularity assumption can not be improved.},
  author       = {Koudjinan, Edmond},
  issn         = {0022-0396},
  journal      = {Journal of Differential Equations},
  keywords     = {Analysis},
  number       = {6},
  pages        = {4720--4750},
  publisher    = {Elsevier},
  title        = {{A KAM theorem for finitely differentiable Hamiltonian systems}},
  doi          = {10.1016/j.jde.2020.03.044},
  volume       = {269},
  year         = {2020},
}

@article{8694,
  abstract     = {We develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps fa(x)=a−x2. We illustrate the effectiveness of our approach by constructing a dynamically defined partition 𝒫 of the parameter interval Ω=[1.4,2] into almost 4×106 subintervals, for each of which we compute to high precision the orbits of the critical points up to some time N and other dynamically relevant quantities, several of which can vary greatly, possibly spanning several orders of magnitude. We also subdivide 𝒫 into a family 𝒫+ of intervals, which we call stochastic intervals, and a family 𝒫− of intervals, which we call regular intervals. We numerically prove that each interval ω∈𝒫+ has an escape time, which roughly means that some iterate of the critical point taken over all the parameters in ω has considerable width in the phase space. This suggests, in turn, that most parameters belonging to the intervals in 𝒫+ are stochastic and most parameters belonging to the intervals in 𝒫− are regular, thus the names. We prove that the intervals in 𝒫+ occupy almost 90% of the total measure of Ω. The software and the data are freely available at http://www.pawelpilarczyk.com/quadr/, and a web page is provided for carrying out the calculations. The ideas and procedures can be easily generalized to apply to other parameterized families of dynamical systems.},
  author       = {Golmakani, Ali and Koudjinan, Edmond and Luzzatto, Stefano and Pilarczyk, Pawel},
  journal      = {Chaos},
  number       = {7},
  publisher    = {AIP},
  title        = {{Rigorous numerics for critical orbits in the quadratic family}},
  doi          = {10.1063/5.0012822},
  volume       = {30},
  year         = {2020},
}

@techreport{8695,
  abstract     = {A look at international activities on Open Science reveals a broad spectrum from individual institutional policies to national action plans. The present Recommendations for a National Open Science Strategy in Austria are based on these international initiatives and present practical considerations for their coordinated implementation with regard to strategic developments in research, technology and innovation (RTI) in Austria until 2030. They are addressed to all relevant actors in the RTI system, in particular to Research Performing Organisations, Research Funding Organisations, Research Policy, memory institutions such as Libraries and Researchers. The recommendation paper was developed from 2018 to 2020 by the OANA working group "Open Science Strategy" and published for the first time in spring 2020 for a public consultation. The now available final version of the recommendation document, which contains feedback and comments from the consultation, is intended to provide an impetus for further discussion and implementation of Open Science in Austria and serves as a contribution and basis for a potential national Open Science Strategy in Austria. The document builds on the diverse expertise of the authors (academia, administration, library and archive, information technology, science policy, funding system, etc.) and reflects their personal experiences and opinions.},
  author       = {Mayer, Katja and Rieck, Katharina and Reichmann, Stefan and Danowski, Patrick and Graschopf, Anton and König, Thomas and Kraker, Peter and Lehner, Patrick and Reckling, Falk and Ross-Hellauer, Tony and Spichtinger, Daniel and Tzatzanis, Michalis and Schürz, Stefanie},
  pages        = {36},
  publisher    = {OANA},
  title        = {{Empfehlungen für eine nationale Open Science Strategie in Österreich / Recommendations for a National Open Science Strategy in Austria}},
  doi          = {10.5281/ZENODO.4109242},
  year         = {2020},
}

@article{8698,
  abstract     = {The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional neural activity patterns. Despite progress in statistical modeling of neural responses and deep learning, current approaches either do not scale to large neural populations or cannot be implemented using biologically realistic mechanisms. Inspired by the sparse and random connectivity of real neuronal circuits, we present a model for neural codes that accurately estimates the likelihood of individual spiking patterns and has a straightforward, scalable, efficient, learnable, and realistic neural implementation. This model’s performance on simultaneously recorded spiking activity of >100 neurons in the monkey visual and prefrontal cortices is comparable with or better than that of state-of-the-art models. Importantly, the model can be learned using a small number of samples and using a local learning rule that utilizes noise intrinsic to neural circuits. Slower, structural changes in random connectivity, consistent with rewiring and pruning processes, further improve the efficiency and sparseness of the resulting neural representations. Our results merge insights from neuroanatomy, machine learning, and theoretical neuroscience to suggest random sparse connectivity as a key design principle for neuronal computation.},
  author       = {Maoz, Ori and Tkačik, Gašper and Esteki, Mohamad Saleh and Kiani, Roozbeh and Schneidman, Elad},
  issn         = {1091-6490},
  journal      = {Proceedings of the National Academy of Sciences of the United States of America},
  number       = {40},
  pages        = {25066--25073},
  publisher    = {National Academy of Sciences},
  title        = {{Learning probabilistic neural representations with randomly connected circuits}},
  doi          = {10.1073/pnas.1912804117},
  volume       = {117},
  year         = {2020},
}

@article{8699,
  abstract     = {In the high spin–orbit-coupled Sr2IrO4, the high sensitivity of the ground state to the details of the local lattice structure shows a large potential for the manipulation of the functional properties by inducing local lattice distortions. We use epitaxial strain to modify the Ir–O bond geometry in Sr2IrO4 and perform momentum-dependent resonant inelastic X-ray scattering (RIXS) at the metal and at the ligand sites to unveil the response of the low-energy elementary excitations. We observe that the pseudospin-wave dispersion for tensile-strained Sr2IrO4 films displays large softening along the [h,0] direction, while along the [h,h] direction it shows hardening. This evolution reveals a renormalization of the magnetic interactions caused by a strain-driven cross-over from anisotropic to isotropic interactions between the magnetic moments. Moreover, we detect dispersive electron–hole pair excitations which shift to lower (higher) energies upon compressive (tensile) strain, manifesting a reduction (increase) in the size of the charge gap. This behavior shows an intimate coupling between charge excitations and lattice distortions in Sr2IrO4, originating from the modified hopping elements between the t2g orbitals. Our work highlights the central role played by the lattice degrees of freedom in determining both the pseudospin and charge excitations of Sr2IrO4 and provides valuable information toward the control of the ground state of complex oxides in the presence of high spin–orbit coupling.},
  author       = {Paris, Eugenio and Tseng, Yi and Paerschke, Ekaterina and Zhang, Wenliang and Upton, Mary H and Efimenko, Anna and Rolfs, Katharina and McNally, Daniel E and Maurel, Laura and Naamneh, Muntaser and Caputo, Marco and Strocov, Vladimir N and Wang, Zhiming and Casa, Diego and Schneider, Christof W and Pomjakushina, Ekaterina and Wohlfeld, Krzysztof and Radovic, Milan and Schmitt, Thorsten},
  issn         = {1091-6490},
  journal      = {Proceedings of the National Academy of Sciences of the United States of America},
  number       = {40},
  pages        = {24764--24770},
  publisher    = {National Academy of Sciences},
  title        = {{Strain engineering of the charge and spin-orbital interactions in Sr2IrO4}},
  doi          = {10.1073/pnas.2012043117},
  volume       = {117},
  year         = {2020},
}

@article{8700,
  abstract     = {Translation termination is a finishing step of protein biosynthesis. The significant role in this process belongs not only to protein factors of translation termination but also to the nearest nucleotide environment of stop codons. There are numerous descriptions of stop codons readthrough, which is due to specific nucleotide sequences behind them. However, represented data are segmental and don’t explain the mechanism of the nucleotide context influence on translation termination. It is well known that stop codon UAA usage is preferential for A/T-rich genes, and UAG, UGA—for G/C-rich genes, which is related to an expression level of these genes. We investigated the connection between a frequency of nucleotides occurrence in 3' area of stop codons in the human genome and their influence on translation termination efficiency. We found that 3' context motif, which is cognate to the sequence of a stop codon, stimulates translation termination. At the same time, the nucleotide composition of 3' sequence that differs from stop codon, decreases translation termination efficiency.},
  author       = {Sokolova, E. E. and Vlasov, Petr and Egorova, T. V. and Shuvalov, A. V. and Alkalaeva, E. Z.},
  issn         = {1608-3245},
  journal      = {Molecular Biology},
  number       = {5},
  pages        = {739--748},
  publisher    = {Springer Nature},
  title        = {{The influence of A/G composition of 3' stop codon contexts on translation termination efficiency in eukaryotes}},
  doi          = {10.1134/S0026893320050088},
  volume       = {54},
  year         = {2020},
}

@article{8701,
  abstract     = {Translation termination is a finishing step of protein biosynthesis. The significant role in this process belongs not only to protein factors of translation termination but also to the nearest nucleotide environment of stop codons. There are numerous descriptions of stop codons readthrough, which is due to specific nucleotide sequences behind them. However, represented data are segmental and don’t explain the mechanism of the nucleotide context influence on translation termination. It is well known that stop codon UAA usage is preferential for A/T-rich genes, and UAG, UGA—for G/C-rich genes, which is related to an expression level of these genes. We investigated the connection between a frequency of nucleotides occurrence in 3' area of stop codons in the human genome and their influence on translation termination efficiency. We found that 3' context motif, which is cognate to the sequence of a stop codon, stimulates translation termination. At the same time, the nucleotide composition of 3' sequence that differs from stop codon, decreases translation termination efficiency.},
  author       = {Sokolova, E. E. and Vlasov, Petr and Egorova, T. V. and Shuvalov, A. V. and Alkalaeva, E. Z.},
  issn         = {0026-8984},
  journal      = {Molekuliarnaia biologiia},
  number       = {5},
  pages        = {837--848},
  publisher    = {Russian Academy of Sciences},
  title        = {{The influence of A/G composition of 3' stop codon contexts on translation termination efficiency in eukaryotes}},
  doi          = {10.31857/S0026898420050080},
  volume       = {54},
  year         = {2020},
}

@inproceedings{8704,
  abstract     = {Traditional robotic control suits require profound task-specific knowledge for designing, building and testing control software. The rise of Deep Learning has enabled end-to-end solutions to be learned entirely from data, requiring minimal knowledge about the application area. We design a learning scheme to train end-to-end linear dynamical systems (LDS)s by gradient descent in imitation learning robotic domains. We introduce a new regularization loss component together with a learning algorithm that improves the stability of the learned autonomous system, by forcing the eigenvalues of the internal state updates of an LDS to be negative reals. We evaluate our approach on a series of real-life and simulated robotic experiments, in comparison to linear and nonlinear Recurrent Neural Network (RNN) architectures. Our results show that our stabilizing method significantly improves test performance of LDS, enabling such linear models to match the performance of contemporary nonlinear RNN architectures. A video of the obstacle avoidance performance of our method on a mobile robot, in unseen environments, compared to other methods can be viewed at https://youtu.be/mhEsCoNao5E.},
  author       = {Lechner, Mathias and Hasani, Ramin and Rus, Daniela and Grosu, Radu},
  booktitle    = {Proceedings - IEEE International Conference on Robotics and Automation},
  isbn         = {9781728173955},
  issn         = {1050-4729},
  location     = {Paris, France},
  pages        = {5446--5452},
  publisher    = {IEEE},
  title        = {{Gershgorin loss stabilizes the recurrent neural network compartment of an end-to-end robot learning scheme}},
  doi          = {10.1109/ICRA40945.2020.9196608},
  year         = {2020},
}

@article{8721,
  abstract     = {Spontaneously arising channels that transport the phytohormone auxin provide positional cues for self-organizing aspects of plant development such as flexible vasculature regeneration or its patterning during leaf venation. The auxin canalization hypothesis proposes a feedback between auxin signaling and transport as the underlying mechanism, but molecular players await discovery. We identified part of the machinery that routes auxin transport. The auxin-regulated receptor CAMEL (Canalization-related Auxin-regulated Malectin-type RLK) together with CANAR (Canalization-related Receptor-like kinase) interact with and phosphorylate PIN auxin transporters. camel and canar mutants are impaired in PIN1 subcellular trafficking and auxin-mediated PIN polarization, which macroscopically manifests as defects in leaf venation and vasculature regeneration after wounding. The CAMEL-CANAR receptor complex is part of the auxin feedback that coordinates polarization of individual cells during auxin canalization.},
  author       = {Hajny, Jakub and Prat, Tomas and Rydza, N and Rodriguez Solovey, Lesia and Tan, Shutang and Verstraeten, Inge and Domjan, David and Mazur, E and Smakowska-Luzan, E and Smet, W and Mor, E and Nolf, J and Yang, B and Grunewald, W and Molnar, Gergely and Belkhadir, Y and De Rybel, B and Friml, Jiří},
  issn         = {1095-9203},
  journal      = {Science},
  number       = {6516},
  pages        = {550--557},
  publisher    = {American Association for the Advancement of Science},
  title        = {{Receptor kinase module targets PIN-dependent auxin transport during canalization}},
  doi          = {10.1126/science.aba3178},
  volume       = {370},
  year         = {2020},
}

@inproceedings{8722,
  abstract     = {Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself. Traditional synchronous Stochastic Gradient Descent (SGD)
achieves good accuracy for a wide variety of tasks, but relies on global synchronization to accumulate the gradients at every training step. In this paper, we propose eager-SGD, which relaxes the global synchronization for
decentralized accumulation. To implement eager-SGD, we propose to use two partial collectives: solo and majority. With solo allreduce, the faster processes contribute their gradients eagerly without waiting for the slower processes, whereas with majority allreduce, at least half of the participants must contribute gradients before continuing, all without using a central parameter server. We theoretically prove the convergence of the algorithms and describe the partial collectives in detail. Experimental results on load-imbalanced environments (CIFAR-10, ImageNet, and UCF101 datasets) show
that eager-SGD achieves 1.27x speedup over the state-of-the-art synchronous SGD, without losing accuracy.},
  author       = {Li, Shigang and Tal Ben-Nun, Tal Ben-Nun and Girolamo, Salvatore Di and Alistarh, Dan-Adrian and Hoefler, Torsten},
  booktitle    = {Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming},
  location     = {San Diego, CA, United States},
  pages        = {45--61},
  publisher    = {Association for Computing Machinery},
  title        = {{Taming unbalanced training workloads in deep learning with partial collective operations}},
  doi          = {10.1145/3332466.3374528},
  year         = {2020},
}

