@inproceedings{15077, abstract = {We consider the following dynamic load-balancing process: given an underlying graph G with n nodes, in each step t≥ 0, one unit of load is created, and placed at a randomly chosen graph node. In the same step, the chosen node picks a random neighbor, and the two nodes balance their loads by averaging them. We are interested in the expected gap between the minimum and maximum loads at nodes as the process progresses, and its dependence on n and on the graph structure. Variants of the above graphical balanced allocation process have been studied previously by Peres, Talwar, and Wieder [Peres et al., 2015], and by Sauerwald and Sun [Sauerwald and Sun, 2015]. These authors left as open the question of characterizing the gap in the case of cycle graphs in the dynamic case, where weights are created during the algorithm’s execution. For this case, the only known upper bound is of 𝒪(n log n), following from a majorization argument due to [Peres et al., 2015], which analyzes a related graphical allocation process. In this paper, we provide an upper bound of 𝒪 (√n log n) on the expected gap of the above process for cycles of length n. We introduce a new potential analysis technique, which enables us to bound the difference in load between k-hop neighbors on the cycle, for any k ≤ n/2. We complement this with a "gap covering" argument, which bounds the maximum value of the gap by bounding its value across all possible subsets of a certain structure, and recursively bounding the gaps within each subset. We provide analytical and experimental evidence that our upper bound on the gap is tight up to a logarithmic factor.}, author = {Alistarh, Dan-Adrian and Nadiradze, Giorgi and Sabour, Amirmojtaba}, booktitle = {47th International Colloquium on Automata, Languages, and Programming}, location = {Saarbrücken, Germany, Virtual}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Dynamic averaging load balancing on cycles}}, doi = {10.4230/LIPIcs.ICALP.2020.7}, volume = {168}, year = {2020}, } @inproceedings{15082, abstract = {Two plane drawings of geometric graphs on the same set of points are called disjoint compatible if their union is plane and they do not have an edge in common. For a given set S of 2n points two plane drawings of perfect matchings M1 and M2 (which do not need to be disjoint nor compatible) are disjoint tree-compatible if there exists a plane drawing of a spanning tree T on S which is disjoint compatible to both M1 and M2. We show that the graph of all disjoint tree-compatible perfect geometric matchings on 2n points in convex position is connected if and only if 2n ≥ 10. Moreover, in that case the diameter of this graph is either 4 or 5, independent of n.}, author = {Aichholzer, Oswin and Obmann, Julia and Patak, Pavel and Perz, Daniel and Tkadlec, Josef}, booktitle = {36th European Workshop on Computational Geometry}, location = {Würzburg, Germany, Virtual}, title = {{Disjoint tree-compatible plane perfect matchings}}, year = {2020}, } @misc{13056, abstract = {This datasets comprises all data shown in plots of the submitted article "Converting microwave and telecom photons with a silicon photonic nanomechanical interface". Additional raw data are available from the corresponding author on reasonable request.}, author = {Arnold, Georg M and Wulf, Matthias and Barzanjeh, Shabir and Redchenko, Elena and Rueda Sanchez, Alfredo R and Hease, William J and Hassani, Farid and Fink, Johannes M}, publisher = {Zenodo}, title = {{Converting microwave and telecom photons with a silicon photonic nanomechanical interface}}, doi = {10.5281/ZENODO.3961561}, year = {2020}, } @misc{13060, abstract = {Coinfections with multiple pathogens can result in complex within-host dynamics affecting virulence and transmission. Whilst multiple infections are intensively studied in solitary hosts, it is so far unresolved how social host interactions interfere with pathogen competition, and if this depends on coinfection diversity. We studied how the collective disease defenses of ants – their social immunity ­– influence pathogen competition in coinfections of same or different fungal pathogen species. Social immunity reduced virulence for all pathogen combinations, but interfered with spore production only in different-species coinfections. Here, it decreased overall pathogen sporulation success, whilst simultaneously increasing co-sporulation on individual cadavers and maintaining a higher pathogen diversity at the community-level. Mathematical modeling revealed that host sanitary care alone can modulate competitive outcomes between pathogens, giving advantage to fast-germinating, thus less grooming-sensitive ones. Host social interactions can hence modulate infection dynamics in coinfected group members, thereby altering pathogen communities at the host- and population-level.}, author = {Milutinovic, Barbara and Stock, Miriam and Grasse, Anna V and Naderlinger, Elisabeth and Hilbe, Christian and Cremer, Sylvia}, publisher = {Dryad}, title = {{Social immunity modulates competition between coinfecting pathogens}}, doi = {10.5061/DRYAD.CRJDFN318}, year = {2020}, } @misc{13065, abstract = {Domestication is a human-induced selection process that imprints the genomes of domesticated populations over a short evolutionary time scale, and that occurs in a given demographic context. Reconstructing historical gene flow, effective population size changes and their timing is therefore of fundamental interest to understand how plant demography and human selection jointly shape genomic divergence during domestication. Yet, the comparison under a single statistical framework of independent domestication histories across different crop species has been little evaluated so far. Thus, it is unclear whether domestication leads to convergent demographic changes that similarly affect crop genomes. To address this question, we used existing and new transcriptome data on three crop species of Solanaceae (eggplant, pepper and tomato), together with their close wild relatives. We fitted twelve demographic models of increasing complexity on the unfolded joint allele frequency spectrum for each wild/crop pair, and we found evidence for both shared and species-specific demographic processes between species. A convergent history of domestication with gene-flow was inferred for all three species, along with evidence of strong reduction in the effective population size during the cultivation stage of tomato and pepper. The absence of any reduction in size of the crop in eggplant stands out from the classical view of the domestication process; as does the existence of a “protracted period” of management before cultivation. Our results also suggest divergent management strategies of modern cultivars among species as their current demography substantially differs. Finally, the timing of domestication is species-specific and supported by the few historical records available.}, author = {Arnoux, Stephanie and Fraisse, Christelle and Sauvage, Christopher}, publisher = {Dryad}, title = {{VCF files of synonymous SNPs related to: Genomic inference of complex domestication histories in three Solanaceae species}}, doi = {10.5061/DRYAD.Q2BVQ83HD}, year = {2020}, } @misc{13070, abstract = {This dataset comprises all data shown in the figures of the submitted article "Surpassing the resistance quantum with a geometric superinductor". Additional raw data are available from the corresponding author on reasonable request.}, author = {Peruzzo, Matilda and Trioni, Andrea and Hassani, Farid and Zemlicka, Martin and Fink, Johannes M}, publisher = {Zenodo}, title = {{Surpassing the resistance quantum with a geometric superinductor}}, doi = {10.5281/ZENODO.4052882}, year = {2020}, } @misc{13071, abstract = {This dataset comprises all data shown in the plots of the main part of the submitted article "Bidirectional Electro-Optic Wavelength Conversion in the Quantum Ground State". Additional raw data are available from the corresponding author on reasonable request.}, author = {Hease, William J and Rueda Sanchez, Alfredo R and Sahu, Rishabh and Wulf, Matthias and Arnold, Georg M and Schwefel, Harald and Fink, Johannes M}, publisher = {Zenodo}, title = {{Bidirectional electro-optic wavelength conversion in the quantum ground state}}, doi = {10.5281/ZENODO.4266025}, year = {2020}, } @misc{13073, abstract = {The Mytilus complex of marine mussel species forms a mosaic of hybrid zones, found across temperate regions of the globe. This allows us to study "replicated" instances of secondary contact between closely-related species. Previous work on this complex has shown that local introgression is both widespread and highly heterogeneous, and has identified SNPs that are outliers of differentiation between lineages. Here, we developed an ancestry-informative panel of such SNPs. We then compared their frequencies in newly-sampled populations, including samples from within the hybrid zones, and parental populations at different distances from the contact. Results show that close to the hybrid zones, some outlier loci are near to fixation for the heterospecific allele, suggesting enhanced local introgression, or the local sweep of a shared ancestral allele. Conversely, genomic cline analyses, treating local parental populations as the reference, reveal a globally high concordance among loci, albeit with a few signals of asymmetric introgression. Enhanced local introgression at specific loci is consistent with the early transfer of adaptive variants after contact, possibly including asymmetric bi-stable variants (Dobzhansky-Muller incompatibilities), or haplotypes loaded with fewer deleterious mutations. Having escaped one barrier, however, these variants can be trapped or delayed at the next barrier, confining the introgression locally. These results shed light on the decay of species barriers during phases of contact.}, author = {Simon, Alexis and Fraisse, Christelle and El Ayari, Tahani and Liautard-Haag, Cathy and Strelkov, Petr and Welch, John and Bierne, Nicolas}, publisher = {Dryad}, title = {{How do species barriers decay? concordance and local introgression in mosaic hybrid zones of mussels}}, doi = {10.5061/DRYAD.R4XGXD29N}, year = {2020}, } @article{14125, abstract = {Motivation: Recent technological advances have led to an increase in the production and availability of single-cell data. The ability to integrate a set of multi-technology measurements would allow the identification of biologically or clinically meaningful observations through the unification of the perspectives afforded by each technology. In most cases, however, profiling technologies consume the used cells and thus pairwise correspondences between datasets are lost. Due to the sheer size single-cell datasets can acquire, scalable algorithms that are able to universally match single-cell measurements carried out in one cell to its corresponding sibling in another technology are needed. Results: We propose Single-Cell data Integration via Matching (SCIM), a scalable approach to recover such correspondences in two or more technologies. SCIM assumes that cells share a common (low-dimensional) underlying structure and that the underlying cell distribution is approximately constant across technologies. It constructs a technology-invariant latent space using an autoencoder framework with an adversarial objective. Multi-modal datasets are integrated by pairing cells across technologies using a bipartite matching scheme that operates on the low-dimensional latent representations. We evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell matches derived by SCIM reflect the same pseudotime on the simulated dataset. Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample and a human bone marrow sample, where we pair cells from a scRNA dataset to their sibling cells in a CyTOF dataset achieving 90% and 78% cell-matching accuracy for each one of the samples, respectively.}, author = {Stark, Stefan G and Ficek, Joanna and Locatello, Francesco and Bonilla, Ximena and Chevrier, Stéphane and Singer, Franziska and Aebersold, Rudolf and Al-Quaddoomi, Faisal S and Albinus, Jonas and Alborelli, Ilaria and Andani, Sonali and Attinger, Per-Olof and Bacac, Marina and Baumhoer, Daniel and Beck-Schimmer, Beatrice and Beerenwinkel, Niko and Beisel, Christian and Bernasconi, Lara and Bertolini, Anne and Bodenmiller, Bernd and Bonilla, Ximena and Casanova, Ruben and Chevrier, Stéphane and Chicherova, Natalia and D'Costa, Maya and Danenberg, Esther and Davidson, Natalie and gan, Monica-Andreea Dră and Dummer, Reinhard and Engler, Stefanie and Erkens, Martin and Eschbach, Katja and Esposito, Cinzia and Fedier, André and Ferreira, Pedro and Ficek, Joanna and Frei, Anja L and Frey, Bruno and Goetze, Sandra and Grob, Linda and Gut, Gabriele and Günther, Detlef and Haberecker, Martina and Haeuptle, Pirmin and Heinzelmann-Schwarz, Viola and Herter, Sylvia and Holtackers, Rene and Huesser, Tamara and Irmisch, Anja and Jacob, Francis and Jacobs, Andrea and Jaeger, Tim M and Jahn, Katharina and James, Alva R and Jermann, Philip M and Kahles, André and Kahraman, Abdullah and Koelzer, Viktor H and Kuebler, Werner and Kuipers, Jack and Kunze, Christian P and Kurzeder, Christian and Lehmann, Kjong-Van and Levesque, Mitchell and Lugert, Sebastian and Maass, Gerd and Manz, Markus and Markolin, Philipp and Mena, Julien and Menzel, Ulrike and Metzler, Julian M and Miglino, Nicola and Milani, Emanuela S and Moch, Holger and Muenst, Simone and Murri, Riccardo and Ng, Charlotte KY and Nicolet, Stefan and Nowak, Marta and Pedrioli, Patrick GA and Pelkmans, Lucas and Piscuoglio, Salvatore and Prummer, Michael and Ritter, Mathilde and Rommel, Christian and Rosano-González, María L and Rätsch, Gunnar and Santacroce, Natascha and Castillo, Jacobo Sarabia del and Schlenker, Ramona and Schwalie, Petra C and Schwan, Severin and Schär, Tobias and Senti, Gabriela and Singer, Franziska and Sivapatham, Sujana and Snijder, Berend and Sobottka, Bettina and Sreedharan, Vipin T and Stark, Stefan and Stekhoven, Daniel J and Theocharides, Alexandre PA and Thomas, Tinu M and Tolnay, Markus and Tosevski, Vinko and Toussaint, Nora C and Tuncel, Mustafa A and Tusup, Marina and Drogen, Audrey Van and Vetter, Marcus and Vlajnic, Tatjana and Weber, Sandra and Weber, Walter P and Wegmann, Rebekka and Weller, Michael and Wendt, Fabian and Wey, Norbert and Wicki, Andreas and Wollscheid, Bernd and Yu, Shuqing and Ziegler, Johanna and Zimmermann, Marc and Zoche, Martin and Zuend, Gregor and Rätsch, Gunnar and Lehmann, Kjong-Van}, issn = {1367-4811}, journal = {Bioinformatics}, keywords = {Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability}, number = {Supplement_2}, pages = {i919--i927}, publisher = {Oxford University Press}, title = {{SCIM: Universal single-cell matching with unpaired feature sets}}, doi = {10.1093/bioinformatics/btaa843}, volume = {36}, year = {2020}, } @inproceedings{14186, abstract = {The goal of the unsupervised learning of disentangled representations is to separate the independent explanatory factors of variation in the data without access to supervision. In this paper, we summarize the results of Locatello et al., 2019, and focus on their implications for practitioners. We discuss the theoretical result showing that the unsupervised learning of disentangled representations is fundamentally impossible without inductive biases and the practical challenges it entails. Finally, we comment on our experimental findings, highlighting the limitations of state-of-the-art approaches and directions for future research.}, author = {Locatello, Francesco and Bauer, Stefan and Lucic, Mario and Rätsch, Gunnar and Gelly, Sylvain and Schölkopf, Bernhard and Bachem, Olivier}, booktitle = {The 34th AAAI Conference on Artificial Intelligence}, isbn = {9781577358350}, issn = {2374-3468}, location = {New York, NY, United States}, number = {9}, pages = {13681--13684}, publisher = {Association for the Advancement of Artificial Intelligence}, title = {{A commentary on the unsupervised learning of disentangled representations}}, doi = {10.1609/aaai.v34i09.7120}, volume = {34}, year = {2020}, } @inproceedings{14187, abstract = {We propose a novel Stochastic Frank-Wolfe (a.k.a. conditional gradient) algorithm for constrained smooth finite-sum minimization with a generalized linear prediction/structure. This class of problems includes empirical risk minimization with sparse, low-rank, or other structured constraints. The proposed method is simple to implement, does not require step-size tuning, and has a constant per-iteration cost that is independent of the dataset size. Furthermore, as a byproduct of the method we obtain a stochastic estimator of the Frank-Wolfe gap that can be used as a stopping criterion. Depending on the setting, the proposed method matches or improves on the best computational guarantees for Stochastic Frank-Wolfe algorithms. Benchmarks on several datasets highlight different regimes in which the proposed method exhibits a faster empirical convergence than related methods. Finally, we provide an implementation of all considered methods in an open-source package.}, author = {Négiar, Geoffrey and Dresdner, Gideon and Tsai, Alicia and Ghaoui, Laurent El and Locatello, Francesco and Freund, Robert M. and Pedregosa, Fabian}, booktitle = {Proceedings of the 37th International Conference on Machine Learning}, location = {Virtual}, pages = {7253--7262}, title = {{Stochastic Frank-Wolfe for constrained finite-sum minimization}}, volume = {119}, year = {2020}, } @inproceedings{14188, abstract = {Intelligent agents should be able to learn useful representations by observing changes in their environment. We model such observations as pairs of non-i.i.d. images sharing at least one of the underlying factors of variation. First, we theoretically show that only knowing how many factors have changed, but not which ones, is sufficient to learn disentangled representations. Second, we provide practical algorithms that learn disentangled representations from pairs of images without requiring annotation of groups, individual factors, or the number of factors that have changed. Third, we perform a large-scale empirical study and show that such pairs of observations are sufficient to reliably learn disentangled representations on several benchmark data sets. Finally, we evaluate our learned representations and find that they are simultaneously useful on a diverse suite of tasks, including generalization under covariate shifts, fairness, and abstract reasoning. Overall, our results demonstrate that weak supervision enables learning of useful disentangled representations in realistic scenarios.}, author = {Locatello, Francesco and Poole, Ben and Rätsch, Gunnar and Schölkopf, Bernhard and Bachem, Olivier and Tschannen, Michael}, booktitle = {Proceedings of the 37th International Conference on Machine Learning}, location = {Virtual}, pages = {6348–6359}, title = {{Weakly-supervised disentanglement without compromises}}, volume = {119}, year = {2020}, } @article{14195, abstract = {The idea behind the unsupervised learning of disentangled representations is that real-world data is generated by a few explanatory factors of variation which can be recovered by unsupervised learning algorithms. In this paper, we provide a sober look at recent progress in the field and challenge some common assumptions. We first theoretically show that the unsupervised learning of disentangled representations is fundamentally impossible without inductive biases on both the models and the data. Then, we train over 14000 models covering most prominent methods and evaluation metrics in a reproducible large-scale experimental study on eight data sets. We observe that while the different methods successfully enforce properties “encouraged” by the corresponding losses, well-disentangled models seemingly cannot be identified without supervision. Furthermore, different evaluation metrics do not always agree on what should be considered “disentangled” and exhibit systematic differences in the estimation. Finally, increased disentanglement does not seem to necessarily lead to a decreased sample complexity of learning for downstream tasks. Our results suggest that future work on disentanglement learning should be explicit about the role of inductive biases and (implicit) supervision, investigate concrete benefits of enforcing disentanglement of the learned representations, and consider a reproducible experimental setup covering several data sets.}, author = {Locatello, Francesco and Bauer, Stefan and Lucic, Mario and Rätsch, Gunnar and Gelly, Sylvain and Schölkopf, Bernhard and Bachem, Olivier}, journal = {Journal of Machine Learning Research}, publisher = {MIT Press}, title = {{A sober look at the unsupervised learning of disentangled representations and their evaluation}}, volume = {21}, year = {2020}, } @inproceedings{9001, abstract = {Quantum illumination is a sensing technique that employs entangled signal-idler beams to improve the detection efficiency of low-reflectivity objects in environments with large thermal noise. The advantage over classical strategies is evident at low signal brightness, a feature which could make the protocol an ideal prototype for non-invasive scanning or low-power short-range radar. Here we experimentally investigate the concept of quantum illumination at microwave frequencies, by generating entangled fields using a Josephson parametric converter which are then amplified to illuminate a room-temperature object at a distance of 1 meter. Starting from experimental data, we simulate the case of perfect idler photon number detection, which results in a quantum advantage compared to the relative classical benchmark. Our results highlight the opportunities and challenges on the way towards a first room-temperature application of microwave quantum circuits.}, author = {Barzanjeh, Shabir and Pirandola, Stefano and Vitali, David and Fink, Johannes M}, booktitle = {IEEE National Radar Conference - Proceedings}, isbn = {9781728189420}, issn = {1097-5659}, location = {Florence, Italy}, number = {9}, publisher = {IEEE}, title = {{Microwave quantum illumination with a digital phase-conjugated receiver}}, doi = {10.1109/RadarConf2043947.2020.9266397}, volume = {2020}, year = {2020}, } @article{9007, abstract = {Motivated by a recent question of Peyre, we apply the Hardy–Littlewood circle method to count “sufficiently free” rational points of bounded height on arbitrary smooth projective hypersurfaces of low degree that are defined over the rationals.}, author = {Browning, Timothy D and Sawin, Will}, issn = {14208946}, journal = {Commentarii Mathematici Helvetici}, number = {4}, pages = {635--659}, publisher = {European Mathematical Society}, title = {{Free rational points on smooth hypersurfaces}}, doi = {10.4171/CMH/499}, volume = {95}, year = {2020}, } @article{9011, abstract = {Distributed ledgers provide high availability and integrity, making them a key enabler for practical and secure computation of distributed workloads among mutually distrustful parties. Many practical applications also require strong confidentiality, however. This work enhances permissioned and permissionless blockchains with the ability to manage confidential data without forfeiting availability or decentralization. The proposed Calypso architecture addresses two orthogonal challenges confronting modern distributed ledgers: (a) enabling the auditable management of secrets and (b) protecting distributed computations against arbitrage attacks when their results depend on the ordering and secrecy of inputs. Calypso introduces on-chain secrets, a novel abstraction that enforces atomic deposition of an auditable trace whenever users access confidential data. Calypso provides user-controlled consent management that ensures revocation atomicity and accountable anonymity. To enable permissionless deployment, we introduce an incentive scheme and provide users with the option to select their preferred trustees. We evaluated our Calypso prototype with a confidential document-sharing application and a decentralized lottery. Our benchmarks show that transaction-processing latency increases linearly in terms of security (number of trustees) and is in the range of 0.2 to 8 seconds for 16 to 128 trustees.}, author = {Kokoris Kogias, Eleftherios and Alp, Enis Ceyhun and Gasser, Linus and Jovanovic, Philipp and Syta, Ewa and Ford, Bryan}, issn = {2150-8097}, journal = {Proceedings of the VLDB Endowment}, number = {4}, pages = {586--599}, publisher = {Association for Computing Machinery}, title = {{CALYPSO: Private data management for decentralized ledgers}}, doi = {10.14778/3436905.3436917}, volume = {14}, year = {2020}, } @article{9039, abstract = {We give a short and self-contained proof for rates of convergence of the Allen--Cahn equation towards mean curvature flow, assuming that a classical (smooth) solution to the latter exists and starting from well-prepared initial data. Our approach is based on a relative entropy technique. In particular, it does not require a stability analysis for the linearized Allen--Cahn operator. As our analysis also does not rely on the comparison principle, we expect it to be applicable to more complex equations and systems.}, author = {Fischer, Julian L and Laux, Tim and Simon, Theresa M.}, issn = {10957154}, journal = {SIAM Journal on Mathematical Analysis}, number = {6}, pages = {6222--6233}, publisher = {Society for Industrial and Applied Mathematics}, title = {{Convergence rates of the Allen-Cahn equation to mean curvature flow: A short proof based on relative entropies}}, doi = {10.1137/20M1322182}, volume = {52}, year = {2020}, } @inproceedings{9040, abstract = {Machine learning and formal methods have complimentary benefits and drawbacks. In this work, we address the controller-design problem with a combination of techniques from both fields. The use of black-box neural networks in deep reinforcement learning (deep RL) poses a challenge for such a combination. Instead of reasoning formally about the output of deep RL, which we call the wizard, we extract from it a decision-tree based model, which we refer to as the magic book. Using the extracted model as an intermediary, we are able to handle problems that are infeasible for either deep RL or formal methods by themselves. First, we suggest, for the first time, a synthesis procedure that is based on a magic book. We synthesize a stand-alone correct-by-design controller that enjoys the favorable performance of RL. Second, we incorporate a magic book in a bounded model checking (BMC) procedure. BMC allows us to find numerous traces of the plant under the control of the wizard, which a user can use to increase the trustworthiness of the wizard and direct further training.}, author = {Alamdari, Par Alizadeh and Avni, Guy and Henzinger, Thomas A and Lukina, Anna}, booktitle = {Proceedings of the 20th Conference on Formal Methods in Computer-Aided Design}, isbn = {9783854480426}, issn = {2708-7824}, location = {Online Conference}, pages = {138--147}, publisher = {TU Wien Academic Press}, title = {{Formal methods with a touch of magic}}, doi = {10.34727/2020/isbn.978-3-85448-042-6_21}, year = {2020}, } @inbook{9096, author = {Schmid-Hempel, Paul and Cremer, Sylvia M}, booktitle = {Encyclopedia of Social Insects}, editor = {Starr, C}, isbn = {9783319903064}, publisher = {Springer Nature}, title = {{Parasites and Pathogens}}, doi = {10.1007/978-3-319-90306-4_94-1}, year = {2020}, } @inproceedings{9103, abstract = {We introduce LRT-NG, a set of techniques and an associated toolset that computes a reachtube (an over-approximation of the set of reachable states over a given time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the state-of-the-art Langrangian Reachability and its associated tool LRT. From a theoretical perspective, LRT-NG is superior to LRT in three ways. First, it uses for the first time an analytically computed metric for the propagated ball which is proven to minimize the ball’s volume. We emphasize that the metric computation is the centerpiece of all bloating-based techniques. Secondly, it computes the next reachset as the intersection of two balls: one based on the Cartesian metric and the other on the new metric. While the two metrics were previously considered opposing approaches, their joint use considerably tightens the reachtubes. Thirdly, it avoids the "wrapping effect" associated with the validated integration of the center of the reachset, by optimally absorbing the interval approximation in the radius of the next ball. From a tool-development perspective, LRT-NG is superior to LRT in two ways. First, it is a standalone tool that no longer relies on CAPD. This required the implementation of the Lohner method and a Runge-Kutta time-propagation method. Secondly, it has an improved interface, allowing the input model and initial conditions to be provided as external input files. Our experiments on a comprehensive set of benchmarks, including two Neural ODEs, demonstrates LRT-NG’s superior performance compared to LRT, CAPD, and Flow*.}, author = {Gruenbacher, Sophie and Cyranka, Jacek and Lechner, Mathias and Islam, Md Ariful and Smolka, Scott A. and Grosu, Radu}, booktitle = {Proceedings of the 59th IEEE Conference on Decision and Control}, isbn = {9781728174471}, issn = {07431546}, location = {Jeju Islang, Korea (South)}, pages = {1556--1563}, publisher = {IEEE}, title = {{Lagrangian reachtubes: The next generation}}, doi = {10.1109/CDC42340.2020.9304042}, volume = {2020}, year = {2020}, }