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2022
  • Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder: Explain and improve: LRP-inference fine-tuning for image captioning models. Inf. Fusion 77: 233-246 (2022)
    https://doi.org/10.1016/j.inffus.2021.07.008

  • Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin: Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. Inf. Fusion 77: 261-295 (2022)
    https://doi.org/10.1016/j.inffus.2021.07.015

  • Leila Arras, Ahmed Osman, Wojciech Samek: CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations. Inf. Fusion, Journal Pre-proof
    https://doi.org/10.1016/j.inffus.2021.11.008

2021
  • Hassan El-Hajj, Matteo Valleriani: CIDOC2VEC: Extracting Information from Atomized CIDOC-CRM Humanities Knowledge Graphs. Information 2021 12(12): 503
    https://doi.org/10.3390/info12120503

  • Philipp Benner, Martin Vingron: Quantifying the tissue-specific regulatory information within enhancer DNA sequences. NAR Genomics and Bioinformatics 3(4) (2021)
    https://doi.org/10.1093/nargab/lqab095

  • Philipp Benner: Computing leapfrog regularization paths with applications to large-scale k-mer logistic regression. J. Comput. Biol. 28(6): 560-569 (2021)
    http://doi.org/10.1089/cmb.2020.0284

  • Lily Hügerich, Apoorv Shukla, Georgios Smaragdakis: No-hop: In-network Distributed Hash Tables. ANCS 2021, to appear

  • Leonard Becker, Oliver Hohlfeld, Georgios Smaragdakis: Large Scale Outage Visibility on the Control Plane. StudentWorkshop@CoNext 2021, to appear

  • Jan Malte Hilgefort, Daniel Arp, Konrad Rieck: Spying through Virtual Backgrounds of Video Calls. AISec@CCS 2021: 135-144
    https://doi.org/10.1145/3474369.3486870
    [PDF]

  • Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kordian Gontarska, Lauritz Thamsen: Let’s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. Middleware 2021, to appear
    Preprint [PDF]

  • Sanaz Soltani, Mohammad Shojafar, Habib Mostafaei, Zahra Pooranian, Rahim Tafazolli: Link Latency Attack in Software-Defined Networks. CNSM 2021: 187-193
    [PDF]

  • Kordian Gontarska, Morgan Geldenhuys, Dominik Scheinert, Philipp Wiesner, Andreas Polze, Lauritz Thamsen: Evaluation of Load Prediction Techniques for Distributed Stream Processing. IC2E 2021, to appear
    Preprint [PDF]

  • Niklas W. A. Gebauer, Michael Gastegger, Stefaan S. P. Hessmann, Klaus-Robert Müller, Kristof T. Schütt: Inverse design of 3d molecular structures with conditional generative neural networks. CoRR abs/2109.04824 (2021)
    https://arxiv.org/abs/2109.04824
    [PDF]

  • Thomas Koch, Weifan Jiang, Tao Luo, Petros Gigis, Kevin Vermeulen, Emile Aben, Matt Calder, Ethan Katz-Bassett, Lefteris Manassakis, Georgios Smaragdakis, Narseo Vallina-Rodriguez: Towards an Internet Traffic Map. HotNets 2021, to appear
    Preprint [PDF]

  • Thomas Krenc, Robert Beverly, Georgios Smaragdakis: AS-level BGP Community Usage Classification. Internet Measurement Conference 2021, to appear
    Preprint [PDF]

  • Taha Albakour, Oliver Gasser, Robert Beverly, Georgios Smaragdakis: Third Time’s Not a Charm: Exploiting SNMPv3 for Router Fingerprinting. Internet Measurement Conference 2021, to appear
    Preprint [PDF]

  • Daniel Wagner, Daniel Kopp, Matthias Wichtlhuber, Christoph Dietzel, Oliver Hohlfeld, Georgios Smaragdakis, Anja Feldmann. United We Stand: Collaborative Detection and Mitigation of Amplification DDoS Attacks at Scale. CCS 2021, to appear
    [PDF]

  • Paolo Andrea Erdman, Frank Noé: Identifying optimal cycles in quantum thermal machines with reinforcement-learning. CoRR abs/2108.13525 (2021)
    https://arxiv.org/abs/2108.13525
    [PDF]

  • Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian März, Gitta Kutyniok, Wojciech Samek: Detecting failure modes in image reconstructions with interval neural network uncertainty. Int. J. CARS (2021)
    https://doi.org/10.1007/s11548-021-02482-2
    [PDF]

  • Habib Mostafaei, Shafi Afridi: P4Flow: Monitoring Traffic Flows with Programmable Networks. IEEE Commun. Lett. (Early Access) (2021)
    https://doi.org/10.1109/LCOMM.2021.3109793
    [PDF]

  • Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé: Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Mach. Learn.: Sci. Technol. 2(4): 045016 (2021)
    https://doi.org/10.1088/2632-2153/ac14ad
    [PDF]

  • Tim Hempel, Katarina Elez, Nadine Krüger, Lluís Raich, Jonathan H. Shrimp, Olga Danov, Danny Jonigk, Armin Braun, Min Shen, Matthew D. Hall, Stefan Pöhlmann, Markus Hoffmann, Frank Noé: Synergistic inhibition of SARS-CoV-2 cell entry by otamixaban and covalent protease inhibitors: pre-clinical assessment of pharmacological and molecular properties. Chem. Sci. 2021
    https://doi.org/10.1039/D1SC01494C
    [PDF]

  • Petros Gigis, Matt Calder, Lefteris Manassakis, George Nomikos, Vasileios Kotronis, Xenofontas A. Dimitropoulos, Ethan Katz-Bassett, Georgios Smaragdakis: Seven years in the life of Hypergiants’ off-nets. SIGCOMM 2021: 516-533
    https://doi.org/10.1145/3452296.3472928
    [PDF]

  • N. Alexia Raharinirina, Felix Peppert, Max von Kleist, Christof Schütte, Vikram Sunkara: Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments. Patterns 2:  100332 (2021)
    https://doi.org/10.1016/j.patter.2021.100332
    [PDF]

  • Binger Chen, Ziawasch Abedjan: Interactive Cross-language Code Retrieval with Auto-Encoders. ASE 2021, to appear

  • Gábor E. Gévay, Juan Soto, Volker Markl: Handling Iterations in Distributed Dataflow Systems. ACM Comput. Surv. (2021), to appear

  • Habib Mostafaei, Mohammad Shojafar, Mauro Conti: TEL: Low-Latency Failover Traffic Engineering in Data Plane. IEEE Trans. Netw. Serv. Manag. (Early Access) (2021)
    https://doi.org/10.1109/TNSM.2021.3099620
    Preprint [PDF]

  • Danh Le Phuoc, Thomas Eiter, Anh Le Tuan: A Scalable Reasoning and Learning Approach for Neural-Symbolic Stream Fusion.  AAAI 2021: 4996-5005
    https://ojs.aaai.org/index.php/AAAI/article/view/16633
    [PDF]

  • Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard: High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding. AISTATS 2021: 1963-1971
    http://proceedings.mlr.press/v130/marienwald21a.html
    [PDF]

  • Arne de Wall, Björn Deiseroth, Eleni Tzirita Zacharatou, Jorge-Arnulfo Quiané-Ruiz, Begüm Demir, Volker Markl: Agora-EO: A Unified Ecosystem for Earth Observation – A Vision for Boosting EO Data Literacy –. BiDS 2021
    https://op.europa.eu/en/publication-detail/-/publication/ac7c57e5-b787-11eb-8aca-01aa75ed71a1
    [PDF]

  • Julia Markowski, Rieke Kempfer, Alexander Kukalev, Ibai Irastorza-Azcarate, Gesa Loof, Ana Pombo, Roland F. Schwarz: GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data. Bioinform. 2021
    https://doi.org/10.1093/bioinformatics/btab238
    [PDF]

  • Tim Hempel, Mauricio J. del Razo, Christopher T. Lee, Brynn C. Taylor, Rommie E. Amaro, Frank Noé: Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes. bioRxiv 2021
    https://doi.org/10.1101/2021.03.24.436806
    [PDF]

  • Alexander Kumaigorodski, Clemens Lutz, Volker Markl: Fast CSV Loading Using GPUs and RDMA for In-Memory Data Processing. BTW 2021: 19-38
    https://dl.gi.de/handle/20.500.12116/35792
    [PDF]

  • Elena Beatriz Ouro Paz, Eleni Tzirita Zacharatou, Volker Markl: Towards Resilient Data Management for the Internet of Moving Things. BTW 2021: 279-301
    https://dx.doi.org/10.18420/btw2021-14
    [PDF]

  • Aldo Glielmo, Brooke E. Husic, Alex Rodriguez, Cecilia Clementi, Frank Noé, Allesandro Laio: Unsupervised Learning Methods for Molecular Simulation Data. Chem. Rev. 2021
    https://doi.org/10.1021/acs.chemrev.0c01195
    [PDF]

  • Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Varun Pandey, Harish Doraiswamy, Volker Markl: The Case for Distance-Bounded Spatial Approximations. CIDR 2021
    [PDF]

  • Kilian Runte, Kay Brosien, Charlotte Schubert, Johannes Nordmeyer, Peter Kramer, Stephan Schubert, Felix Berger, Anja Hennemuth, Titus Kuehne, Marcus Kelm, Leonid Goubergrits:  Image-Based Computational Model Predicts Dobutamine-Induced Hemodynamic Changes in Patients With Aortic Coarctation. Circ. Cardiovasc. Imaging. 14(2): e011523 (2021)
    https://doi.org/10.1161/CIRCIMAGING.120.011523
    [PDF]

  • Anja Feldmann, Oliver Gasser, Franziska Lichtblau, Enric Pujol, Ingmar Poese, Christoph Dietzel, Daniel Wagner, Matthias Wichtlhuber, Juan Tapiador, Narseo Vallina-Rodriguez, Oliver Hohlfeld, Georgios Smaragdakis: A Year in Lockdown: How the Waves of COVID-19 Impact Internet Traffic. Commun. ACM 64(7): 101-108 (2021)
    https://doi.org/10.1145/3465212
    [PDF]

  • Tabea Kossen, Pooja Subramaniam, Vince I. Madai, Anja Hennemuth, Kristian Hildebrand, Adam Hilbert, Jan Sobesky, Michelle Livne, Ivana Galinovic, Ahmed A. Khalil, Jochen B. Fiebach, Dietmar Frey: Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks. Comput. Biol. Medicine 131: 104254 (2021)
    https://doi.org/10.1016/j.compbiomed.2021.104254

  • Mauricio J. del Razo, Manuel Dibak, Christoph Schütte, Frank Noé: Multiscale molecular kinetics by coupling Markov state models and reaction-diffusion dynamics. CoRR abs/2103.06889 (2021)
    https://arxiv.org/abs/2103.06889
    [PDF]

  • Robin Winter, Frank Noé, Djork-Arné Clevert: Auto-Encoding Molecular Conformations. CoRR abs/2101.01618 (2021)
    https://arxiv.org/abs/2101.01618
    [PDF]

  • Robin Winter, Frank Noé, Djork-Arné Clevert: Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning. CoRR abs/2104.09856 (2021)
    https://arxiv.org/abs/2104.09856
    [PDF]

  • Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé: Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. CoRR abs/2103.17233 (2021)
    https://arxiv.org/abs/2103.17233
    [PDF]

  • Tuan Le, Marco Bertolini, Frank Noé, Djork-Arné Clevert: Parameterized Hypercomplex Graph Neural Networks for Graph Classification. CoRR abs/2103.16584 (2021)
    https://arxiv.org/abs/2103.16584
    [PDF]

  • Alexander Renz-Wieland, Rainer Gemulla, Zoi Kaoudi, Volker Markl: Replicate or Relocate? Non-Uniform Access in Parameter Servers. CoRR abs/2104.00501 (2021)
    https://arxiv.org/abs/2104.00501
    [PDF]

  • Gencer Sumbul, Arne de Wall, Tristan Kreuziger, Filipe Marcelino, Hugo Costa, Pedro Benevides, Mario Caetano, Begüm Demir, Volker Markl: BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval. CoRR abs/2105.07921 (2021)
    https://arxiv.org/abs/2105.07921
    [PDF]

  • Adrian Michalke, Philipp Marian Grulich, Clemens Lutz, Steffen Zeuch, Volker Markl: An Energy-Efficient Stream Join for the Internet of Things. DaMoN 2021: 8:1-8:6
    https://doi.org/10.1145/3465998.3466005
    [PDF]

  • Manh Nguyen Duc, Anh Le Tuan, Manfred Hauswirth, Danh Le Phuoc: Towards autonomous semantic stream fusion for distributed video streams.  DEBS 2021: 172-175.
    https://doi.org/10.1145/3465480.3467837

  • Siddhant Agarwal, Nicola Tosi, Pan Kessel, Sebastiano Padovan, Doris Breuer, Grégoire Montavon: Towards constraining Mars’ thermal evolution using machine learning. Earth and Space Science 8 (2021)
    https://doi.org/10.1029/2020EA001484
    [PDF]

  • Felipe Gutierrez, Kaustubh Beedkar, Abel Souza, Volker Markl: AdCom: Adaptive Combiner for Streaming Aggregations. EDBT 2021: 409 – 414
    [PDF]

  • Julius Hülsmann, Chiao-Yun Li, Jonas Traub, Volker Markl: Automatic Tuning of Read-Time Tolerances for Optimized On-Demand Data-Streaming from Sensor Nodes. EDBT 2021: 517-522
    [PDF]

  • Mahdi Esmailoghli, Jorge-Arnulfo Quiané-Ruiz, Ziawasch Abedjan: COCOA: COrrelation COefficient-Aware Data Augmentation. EDBT 2021: 331-336
    [PDF]

  • Sergey Redyuk, Zoi Kaoudi, Volker Markl, Sebastian Schelter: Automating Data Quality Validation for Dynamic Data Ingestion. EDBT 2021: 61-72
    [PDF]

  • Osman Musa, Peter Jung, Giuseppe Caire: Plug-And-Play Learned Gaussian-mixture Approximate Message Passing. ICASSP 2021: 4855-4859
    https://doi.org/10.1109/ICASSP39728.2021.9414910
    Preprint [PDF]

  • Gábor E. Gévay, Tilmann Rabl, Sebastian Breß, Loránd Madai-Tahy, Jorge-Arnulfo Quiané-Ruiz, Volker Markl: Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance. ICDE 2021: 1428-1439
    https://doi.org/10.1109/ICDE51399.2021.00127
    [PDF]

  • Philipp Wiesner, Lauritz Thamsen: LEAF: Simulating Large Energy-AwareFog Computing Environments. ICFEC 2021: 29-36
    https://doi.org/10.1109/ICFEC51620.2021.00012
    Preprint [PDF]

  • Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller: Explainable Deep One-Class Classification. ICLR 2021
    https://openreview.net/forum?id=A5VV3UyIQz
    [PDF]

  • Binger Chen, Ziawasch Abedjan: RPT: Effective and Efficient Retrieval of Program Translations from Big Code. ICSE (Companion Volume) 2021: 252-253
    https://doi.org/10.1109/ICSE-Companion52605.2021.00117
    Preprint [PDF]

  • Felix Neutatz, Binger Chen, Ziawasch Abedjan, Eugene Wu: From Cleaning before ML to Cleaning for ML. IEEE Data Eng. Bull. 44(1): 24-33 (2021)
    http://sites.computer.org/debull/A21mar/issue1.htm
    [PDF]

  • Apoorv Shukla, Kevin Hudemann, Zsolt Vági, Lily Hügerich, Georgios Smaragdakis, Artur Hecker, Stefan Schmid, Anja Feldmann: Fix with P6: Verifying Programmable Switches at Runtime. IEEE INFOCOM 2021
    https://doi.org/10.1109/INFOCOM42981.2021.9488772
    [PDF]

  • Matthias Frey, Igor Bjelaković, Sławomir Stańczak: Towards Secure Over-The-Air Computation. IEEE ISIT 2021, to appear
    Preprint [PDF]

  • Habib Mostafaei, Davinder Kumar, Gabriele Lospoto, Marco Chiesa, Giueseppe Di Battista: DeSI: A Decentralized Software-Defined Network Architecture for Internet eXchange Points. IEEE Trans. Netw. Sci. Eng. (2021)
    https://doi.org/10.1109/TNSE.2021.3082575
    [PDF]

  • Masoud Gholami, Florian Schintke: Combining XOR and Partner Checkpointing for Resilient Multilevel Checkpoint/Restart. IPDPS 2021: 277-288
    https://doi.org/10.1109/IPDPS49936.2021.00036

  • Anja Feldmann, Oliver Gasser, Franziska Lichtblau, Enric Pujol, Ingmar Poese, Christoph Dietzel, Daniel Wagner, Matthias Wichtlhuber, Juan Tapiador, Narseo Vallina-Rodriguez, Oliver Hohlfeld, Georgios Smaragdakis: Implications of the COVID-19 Pandemic on the Internet Traffic. ITG-Fachkonferenz “Breitbandversorgung in Deutschland” (2021)
    https://ieeexplore.ieee.org/document/9399711
    [PDF]

  • Brooke E. Husic, Nicholas E. Charron, Dominik Lemm, Jiang Wang, Adrià Pérez, Maciej Majewski, Andreas Krämer, Yaoyi Chen, Simon Olsson, Gianni de Fabritiis, Frank Noé, Cecilia Clementi: Coarse graining molecular dynamics with graph neural networks. J. Chem. Phys. 153(19): 194101 (2020)
    https://doi.org/10.1063/5.0026133
    [PDF]

  • Jiang Wang, Nicholas Charron, Brooke Husic, Simon Olsson, Frank Noé, Cecilia Clementi: Multi-body effects in a coarse-grained protein force field. J. Chem. Phys. 154(16): 164113 (2021)
    https://doi.org/10.1063/5.0041022

  • Luigi Sbailò, Manuel Dibak, Frank Noé: Neural mode jump Monte Carlo. J. Chem. Phys. 154(7): 074101 (2021)
    https://doi.org/10.1063/5.0032346
    Preprint [PDF]

  • Zeno Schätzle, Jan Hermann, Frank Noé: Convergence to the fixed-node limit in deep variational Monte Carlo. J. Chem. Phys. 154(12): 124108 (2021)
    https://doi.org/10.1063/5.0032836
    Preprint [PDF]

  • Stefan Doerr, Maciej Majewski, Adrià Pérez, Andreas Krämer, Cecilia Clementi, Frank Noé, Toni Giorgino, Gianni De Fabritiis: TorchMD: A deep learning framework for molecular simulations. J. Chem. Theory Comp. 17(4): 2355-2363 (2021)
    https://doi.org/10.1021/acs.jctc.0c01343
    Preprint [PDF]

  • Huziel E. Sauceda, Valentin Vassilev-Galindo, Stefan Chmiela, Klaus-Robert Müller, Alexandre Tkatchenko: Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature. Nat. Commun. 12(442) (2021)
    https://doi.org/10.1038/s41467-020-20212-1
    [PDF]

  • Habib Mostafaei, Shafi Afridi, Jemal H. Abawajy: SNR: Network-aware Geo-Distributed Stream Analytics. NEAC@CCGriD 2021: 820-827
    https://doi.org/10.1109/CCGrid51090.2021.00100

  • Vignesh Srinivasan, Arturo Marban, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima: Robustifying Models Against Adversarial Attacks by Langevin Dynamics. Neural Networks 137: 1-17 (2021)
    https://doi.org/10.1016/j.neunet.2020.12.024

  • Manuel Dibak, Leon Klein, Frank Noé: Temperature-steerable flows. NeurIPS (Workshops) 2020
    [PDF]

  • Xenofon Chatziliadis, Eleni Tzirita Zacharatou, Steffen Zeuch, Volker Markl: Monitoring of Stream Processing Engines Beyond the Cloud: an Overview. Open J. Internet Things 7(1): 71-82 (2021)
    https://www.ronpub.com/ojiot/OJIOT_2021v7i1n07_Chatziliadis.html
    [PDF]

  • Dimitrios Giouroukis, Johannes Jestram, Steffen Zeuch, Volker Markl: Streaming Data through the IoT via Actor-Based Semantic Routing Trees. Open J. Internet Things 7(1):59-70 (2021)
    https://www.ronpub.com/ojiot/OJIOT_2021v7i1n06_Giouroukis.html
    [PDF]

  • Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek: Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. 115: 107899 (2021)
    https://doi.org/10.1016/j.patcog.2021.107899
    [PDF]

  • Matteo Valleriani, Beate Federau, Olga Nicolaeva: The Hidden Praeceptor: How Georg Rheticus Taught Geocentric Cosmology to Europe. Perspectives in Science (2021), to appear

  • Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati: On Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models. Phys. Revi. Lett. 126(032001) (2021)
    https://doi.org/10.1103/physrevlett.126.032001
    [PDF]

  • Lluís Raich, Katharina Meier, Judith Günther, Clara D. Christ, Frank Noé, Simon Olsson: Discovery of a hidden transient state in all bromodomain families. PNAS 118(4) (2021)
    https://doi.org/10.1073/pnas.2017427118
    [PDF]

  • Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller: A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE 109(5): 756-795 (2021)
    https://doi.org/10.1109/JPROC.2021.3052449
    [PDF]

  • Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller: Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109(3): 247-278 (2021)
    https://doi.org/10.1109/JPROC.2021.3060483
    [PDF]

  • Ricardo Salazar Diaz, Felix Neutatz, Ziawasch Abedjan: Automated Feature Engineering for Algorithmic Fairness. Proc. VLDB Endow. 14(9): 1694-1702 (2021)
    [PDF]

  • Kaustubh Beedkar, David Brekardin, Jorge Arnulfo Quiane Ruiz, Volker Markl: Compliant Geo-distributed Data Processing in Action. Proc. VLDB Endow. 14(12): 2843-2846 (2021)
    [PDF]

  • Alexander Renz-Wieland, Tobias Drobisch, Zoi Kaoudi, Rainer Gemulla, Volker Markl: Just Move It! Dynamic Parameter Allocation in Action. Proc. VLDB Endow. 14(12): 2707-2710 (2021)
    [PDF]

  • Zihao Chen, Zhizhen Xu, Chen Xu, Juan Soto, Volker Markl, Weining Qian, Aoying Zhou: HyMAC: A Hybrid Matrix Computation System. Proc. VLDB Endow. 14(12): 2699-2702 (2021)
    [PDF]

  • Rudi Poepsel-Lemaitre, Martin Kiefer, Joscha von Hein, Jorge Arnulfo Quiane Ruiz, Volker Markl: In the Land of Data Streams where Synopses are Missing, One Framework to Bring Them All. Proc. VLDB. Endow. 14(10): 1818-1831 (2021)
    [PDF]

  • Felix Neutatz, Felix Bießmann, Ziawasch Abedjan: Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study. SIGMOD Conference 2021: 1345-1358
    https://dl.acm.org/doi/10.1145/3448016.3457295
    Preprint [PDF]

  • Francesco Ventura, Zoi Kaoudi, Jorge Arnulfo Quiane Ruiz, Volker Markl: Expand your Training Limits! Generating and Labeling Jobs for ML-based Data Management. SIGMOD Conference 2021: 1865-1878
    https://doi.org/10.1145/3448016.3457286
    Preprint [PDF]

  • Gábor E. Gévay, Jorge-Arnulfo Quiané-Ruiz, Volker Markl: The Power of Nested Parallelism in Big Data Processing – Hitting Three Flies with One Slap –. SIGMOD Conference 2021: 605-618
    https://doi.org/10.1145/3448016.3457287
    Preprint [PDF]

  • Kaustubh Beedkar, Jorge Quiane-Ruiz, Volker Markl: Compliant Geo-distributed Query Processing. SIGMOD Conference 2021: 181-193
    https://doi.org/10.1145/3448016.3453687
    Preprint [PDF]

  • Sebastian Baunsgaard, Matthias Boehm, Ankit Chaudhary, Behrouz Derakhshan, Stefan Geißelsöder, Philipp Marian Grulich, Michael Hildebrand, Kevin Innerebner, Volker Markl, Claus Neubauer, Sarah Osterburg, Olga Ovcharenko, Sergey Redyuk, Tobias Rieger, Alireza Rezaei Mahdiraji, Sebastian Benjamin Wrede, Steffen Zeuch: ExDRa: Exploratory Data Science on Federated Raw Data. SIGMOD Conference 2021: 2450-2463
    https://doi.org/10.1145/3448016.3457549
    Preprint [PDF]

  • Shuhao Zhang, Yancan Mao, Jiong He, Philipp M. Grulich, Steffen Zeuch, Bingsheng He, Richard T. B. Ma, Volker Markl: Parallelizing Intra-Window Join on Multicores: An Experimental Study. SIGMOD Conference 2021: 2089-2101
    https://doi.org/10.1145/3448016.3452793
    Preprint [PDF]

  • Zihao Chen, Chen Xu, Juan Soto, Volker Markl, Weining Qian, Aoying Zhou: Hybrid Evaluation for Distributed Iterative Matrix Computation. SIGMOD Conference 2021: 300-312
    https://doi.org/10.1145/3448016.3452843
    Preprint [PDF]

  • Jonas Traub, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Volker Markl: Agora: Bringing Together Datasets, Algorithms, Models and More in a Unified Ecosystem [Vision]. SIGMOD Rec. 49(4): 6-11 (2020)
    https://doi.org/10.1145/3456859.3456861
    Preprint [PDF]

  • Wojciech Samek, Leila Arras, Ahmed Osman, Grégoire Montavon, Klaus-Robert Müller: Explaining the Decisions of Convolutional and Recurrent Neural Networks. Mathematical Aspects of Deep Learning. Cambridge University Press 2021: 1-33
2020
  • Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek: Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3400-3413 (2020)
    https://doi.org/10.1109/TNNLS.2019.2944481

  • Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima: Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI 2020: 5842-5850
    https://doi.org/10.1609/aaai.v34i04.6042
    [PDF]

  • Christoph Alt, Aleksandra Gabryszak, Leonhard Hennig: Probing Linguistic Features of Sentence-Level Representations in Neural Relation Extraction. ACL 2020: 1534-1545
    http://dx.doi.org/10.18653/v1/2020.acl-main.140
    [PDF]

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  • Kristof T. Schütt, Stefan Chmiela, O. Anatole von Lilienfeld, Alexandre Tkatchenko, Koji Tsuda, Klaus-Robert Müller: Machine Learning Meets Quantum Physics. Lecture Notes in Physics 968, Springer Cham 2020, ISBN 978-3-030-40245-7
    https://doi.org/10.1007/978-3-030-40245-7

  • Stefan Chmiela, Huziel E. Sauceda, Alexandre Tkatchenko, Klaus-Robert Müller: Accurate Molecular Dynamics Enabled by Efficient Physically-Constrained Machine Learning Approaches. Machine Learning Meets Quantum Physics 2020: 129-154
    https://doi.org/10.1007/978-3-030-40245-7_7

  • Teodora Chitiboi, Mikael Kanski, Lennart Tautz, Anja Hennemuth, Dan Halpern, Mark Sherrid, Leon Axel: Analysis of three-chamber view conventional and tagged cine MRI in patients with suspected hypertrophic cardiomyopathy. Magn. Reson. Mater. Phy. 33: 613–626 (2020)
    https://doi.org/10.1007/s10334-020-00836-6

  • Andreas Mardt, Luca Pasquali, Frank Noé, Hao Wu: Deep learning Markov and Koopman models with physical constraints. MSML 2020: 451-475
    http://proceedings.mlr.press/v107/mardt20a.html

  • PCAWG Transcriptome Core Group, Claudia Calabrese, Natalie R. Davidson, et al.: Genomic basis for RNA alterations in cancer. Nat. 578: 129-136 (2020)
    https://doi.org/10.1038/s41586-020-1970-0

  • The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, P. J. Campbell, G. Getz,  et al.: Pan-cancer analysis of whole genomes. Nat. 578: 82-93 (2020)
    https://doi.org/10.1038/s41586-020-1969-6

  • Thomas B. K. Watkins, Emilia L. Lim, Marina Petkovic, et al.: Pervasive chromosomal instability and karyotype order in tumour evolution. Nat. 587: 126–132 (2020)
    https://doi.org/10.1038/s41586-020-2698-6

  • Jan Hermann, Zeno Schätzle, Frank Noé: Deep-neural-network solution of the electronic Schrödinger equation. Nat. Chem. 12(10): 891-897 (2020)
    https://doi.org/10.1038/s41557-020-0544-y

  • Mihail Bogojeski, Leslie Vogt-Maranto, Mark E. Tuckerman, Klaus-Robert Müller, Kieron Burke: Quantum chemical accuracy from density functional approximations via machine learning. Nat. Commun. 11(5223) (2020)
    https://doi.org/10.1038/s41467-020-19093-1

  • Richard P. Koche, Elias Rodriguez-Fos, Konstantin Helmsauer, et al.: Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma. Nat. Genet. 52: 29–34 (2020)
    https://doi.org/10.1038/s41588-019-0547-z

  • Saioa López, Emilia L. Lim, Stuart Horswell, et al.: Interplay between whole-genome doubling and the accumulation of deleterious alterations in cancer evolution. Nat. Genet. 52(3): 283-293 (2020)
    https://doi.org/10.1038/s41588-020-0584-7

  • Wojciech Samek: Learning with Explainable Trees. Nat. Mach. Intell. 2: 16-17 (2020)
    https://doi.org/10.1038/s42256-019-0142-0

  • Hao Wu, Jonas Köhler, Frank Noé: Stochastic normalizing flows. NeurIPS 2020: 5933-5944
    https://proceedings.neurips.cc/paper/2020/hash/41d80bfc327ef980528426fc810a6d7a-Abstract.html

  • Charlotte Schubert, Gareth Archer, Jo M. Zelis, Sarah Nordmeyer, Kilian Runte, Anja Hennemuth, Felix Berger, Volkmar Falk, Pim A. L. Tonino, Rod Hose, Herman Ter Horst, Titus Kuehne, Marcus Kelm: Wearable devices can predict the outcome of standardized 6-minute walk tests in heart disease. NPJ Digit Med. 3(92) (2020)
    https://doi.org/10.1038/s41746-020-0299-2

  • Felix Sattler, Jackie Ma, Patrick Wagner, David Neumann, Markus Wenzel, Ralf Schäfer, Wojciech Samek, Klaus-Robert Müller, Thomas Wiegand: Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements. NPJ Digit. Med. 3(129) (2020)
    https://doi.org/10.1038/s41746-020-00340-0

  • Nina Rank, Boris Pfahringer, Jörg Kempfert, Christof Stamm, Titus Kühne, Felix Schoenrath, Volkmar Falk, Carsten Eickhoff, Alexander Meyer: Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance. NPJ Digit. Med. 3: 139 (2020)
    https://doi.org/10.1038/s41746-020-00346-8

  • Steffen Zeuch, Eleni Tzirita Zacharatou, Shuhao Zhang, Xenofon Chatziliadis, Ankit Chaudhary, Bonaventura Del Monte, Dimitrios Giouroukis, Philipp M. Grulich, Ariane Ziehn, Volker Markl: NebulaStream: Complex Analytics Beyond the Cloud. Open J. Internet Things 6(1): 66-81 (2020)
    https://www.ronpub.com/ojiot/OJIOT_2020v6i1n07_Zeuch.html
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  • Jacob Kauffmann, Klaus-Robert Müller, Grégoire Montavon: Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models. Pattern Recognit. 101: 107198 (2020)
    https://doi.org/10.1016/j.patcog.2020.107198

  • Laura Marx, Matthias M. F. Gsell, Armin Rund, Federica Caforio, Anton J. Prassl, Gabor Toth-Gayor, Titus Kuehne, Christoph M. Augustin, Gernot Plank: Personalization of electro-mechanical models of the pressure-overloaded left ventricle: fitting of Wind-kessel-type afterload models. Philos. Trans. A Math. Phys. Eng. Sci. 378(2173): 20190342 (2020)
    https://doi.org/10.1098/rsta.2019.0342

  • Kim A. Nicoli, Shinichi Nakajima, Nils Strodthoff, Wojciech Samek, Klaus-Robert Müller, Pan Kessel: Asymptotically Unbiased Estimation of Physical Observables with Neural Samplers. Phys. Rev. E 101(023304) (2020)
    https://doi.org/10.1103/PhysRevE.101.023304

  • Alexander Renz-Wieland, Rainer Gemulla, Steffen Zeuch, Volker Markl: Dynamic Parameter Allocation in Parameter Servers. Proc. VLDB Endow. 13(11): 1877-1890 (2020)
    https://doi.org/10.14778/3407790.3407796
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  • Julius Hülsmann, Jonas Traub, Volker Markl: Demand-based Sensor Data Gathering with Multi-Query Optimization. Proc. VLDB Endow. 13(12): 2801–2804 (2020)
    https://doi.org/10.14778/3415478.3415479
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  • Markus Dreseler, Martin Boissier, Tilmann Rabl, Matthias Uflacker: Quantifying TPC-H Choke Points and Their Optimizations. Proc. VLDB Endow. 13(8): 1206-1220 (2020)
    https://doi.org/10.14778/3389133.338913
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  • Martin Kiefer, Ilias Poulakis, Sebastian Breß, Volker Markl: Scotch: Generating FPGA-Accelerators for Sketching at Line Rate. Proc. VLDB Endow. 14(3): 241-457 (2020)
    https://doi.org/10.14778/3430915.3430919
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  • Jeyhun Karimov, Tilmann Rabl, Volker Markl: AJoin: Ad-hoc Stream Joins at Scale. Proc. VLDB Endow. 13(4): 435-448 (2019)
    https://doi.org/10.14778/3430915.3430919
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  • Milena T. Bagdasarian, Anna Hilsmann, Peter Eisert, Gabriel Curio, Klaus-Robert Müller, Thomas Wiegand, Sebastian Bosse: EEG-Based Assessment of Perceived Realness in Stylized Face Images. QoMEX 2020: 1-4
    https://doi.org/10.1109/QoMEX48832.2020.9123145

  • Philipp Leinen, Malte Esders, Kristof T. Schütt, Christian Wagner, Klaus-Robert Müller, F. Stefan Tautz: Autonomous robotic nanofabrication with reinforced learning. Sci. Adv. 6(36) (2020)
    https://doi.org/10.1126/sciadv.abb6987

  • Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I. Lunze, Wojciech Samek, Tobias Schaeffter: PTB-XL, A Large Publicly Available Electrocardiography Dataset. Sci. Data 7 (2020)
    https://doi.org/10.1038/s41597-020-0495-6

  • Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder: Resolving Challenges in Deep Learning-Based Analyses of Histopathological Images using Explanation Methods. Sci. Rep. 10 (2020)
    https://doi.org/10.1038/s41598-020-62724-2

  • Zamani Maryam, Alejandro Tejedor, Malte Vogl, Florian Kräutli, Matteo Valleriani, Holger Kantz: Evolution and Transformation of Early Modern Cosmological Knowledge: A Network Study. Sci. Rep. 10(19822) (2020)
    https://doi.org/10.1038/s41598-020-76916-3

  • Dong-Ok Won, Klaus-Robert Müller, Seong-Whan Lee: An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real-world conditions. Sci. Robotics 5(46) (2020)
    https://doi.org/10.1126/scirobotics.abb9764

  • Roberto Lalli, Riaz Howey, Dirk Wintergrün: The dynamics of collaboration networks and the history of general relativity, 1925-1970. Scientometrics 122(2): 1129-1170 (2020)
    https://doi.org/10.1007/s11192-019-03327-1

  • Anh Le-Tuan, Conor Hayes, Manfred Hauswirth, Danh Le-Phuoc: Pushing the Scalability of RDF Engines on IoT Edge Devices. Sensors 20(10): 2788 (2020)
    https://doi.org/10.3390/s20102788

  • Muhammad Imran, Gábor E. Gévay, Volker Markl: Distributed Graph Analytics with Datalog Queries in Flink. SFDI/LSGDA@VLDB 2020: 70-83
    https://doi.org/10.1007/978-3-030-61133-0_6
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  • Behrouz Derakhshan, Alireza Rezaei Mahdiraji, Ziawasch Abedjan, Tilmann Rabl, Volker Markl: Optimizing Machine Learning Workloads in Collaborative Environments. SIGMOD Conference 2020: 1701-1716
    https://doi.org/10.1145/3318464.3389715
    Preprint [PDF]

  • Bonaventura Del Monte, Steffen Zeuch, Tilmann Rabl, Volker Markl: Rhino: Efficient Management of Very Large Distributed State for Stream Processing Engines. SIGMOD Conference 2020: 2471-2486
    https://doi.org/10.1145/3318464.3389723
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  • Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl: Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects. SIGMOD Conference 2020: 1633-1649
    https://doi.org/10.1145/3318464.3389705
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  • Philipp M. Grulich, Sebastian Breß, Steffen Zeuch, Jonas Traub, Janis von Bleichert, Zongxiong Chen, Tilmann Rabl, Volker Markl: Grizzly: Efficient Stream Processing Through Adaptive Query Compilation. SIGMOD Conference 2020: 2487-2503
    https://doi.org/10.1145/3318464.3389739
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  • Erwin Quiring, Konrad Rieck: Backdooring and Poisoning Neural Networks with Image-Scaling Attacks. SP Workshops 2020: 41-47
    https://doi.org/10.1109/SPW50608.2020.00024

  • Matthias Ivantsits, Markus Hüllebrand, Hannu Zhang, Peter Kohlmann, Jan-Martin Kuhnigk, Titus Kühne, Stefan O. Schönberg, Anja Hennemuth: Comparison of a Hybrid Mixture Model and a CNN for the Segmentation of Myocardial Pathologies in Delayed Enhancement MRI. M&Ms and EMIDEC/STACOM@MICCAI 2020: 319-327
    https://doi.org/10.1007/978-3-030-68107-4_32

  • Jürgen Renn: The evolution of knowledge: rethinking science for the Anthropocene. Princeton University Press 2020, ISBN 978-0-691-17198-2

  • Robert Lalli, Riaz Howey, Dirk Wintergrün: The socio-epistemic networks of general relativity, 1925–1970. The Renaissance of General Relativity in Context 2020: 15-84
    https://doi.org/10.1007/978-3-030-50754-1_2

  • Oliver Eberle, Jochen Büttner, Florian Kräutli, Klaus-Robert Müller, Matteo Valleriani, Grégoire Montavon: Building and Interpreting Deep Similarity Models. TPAMI 2020, early access
    https://doi.org/10.1109/TPAMI.2020.3020738

  • Felix Sattler, Klaus-Robert Müller, Wojciech Samek: Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints. Trans. Neural Networks Learn. Syst. 31(9): 1-13 (2020)
    https://doi.org/10.1109/TNNLS.2020.3015958

  • Luis Oala, Cosmas Heiß, Jan Macdonald, Maximilian März, Wojciech Samek, Gitta Kutyniok: Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty. UDL@ICML 2020
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  • Erwin Quiring, David Klein, Daniel Arp, Martin Johns, Konrad Rieck: Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning. USENIX Security Symposium 2020: 1363-1380
    https://www.usenix.org/conference/usenixsecurity20/presentation/quiring

  • Sebastian Kruse, Zoi Kaoudi, Bertty Contreras-Rojas, Sanjay Chawla, Felix Naumann, Jorge-Arnulfo Quiané-Ruiz: RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. VLDB J. 29(6): 1287-1310 (2020)
    https://doi.org/10.1007/s00778-020-00612-x
    [PDF]